old_vignette/Getters.md
In caravagn/revolver: REVOLVER - Repeated Evolution in Cancer
Getter functions
Giulio Caravagna
May 1, 2019
# Load REVOLVER
library(revolver)
## [ ctree - Clone Trees in cancer ]
## Author : Giulio Caravagna <gcaravagn@gmail.com>
## GitHub : caravagn/ctree
##
## Available datasets ~ use data('xxx', package='REVOLVER_datasets') to load dataset 'xxx'
##
## ◉ TRACERx_NEJM_2017 Mutations from TRACERx lung (NEJM2017, PMID: 28445112). n = 99 patients, multi-region WES.
## ◉ TRACERx_NEJM_2017_REVOLVER REVOLVER analysis of TRACERx_NEJM_2017.
## [ REVOLVER - Repeated Evolution in Cancer ]
## Author : Giulio Caravagna <gcaravagn@gmail.com>
## GitHub : caravagn/revolver
In this vignette we make use of one of the cohort objects released with
the tool.
# Data released in the 'evoverse.datasets'
data('TRACERx_NEJM_2017_REVOLVER', package = 'evoverse.datasets')
# We can use S3 object functions to retrieve simple information about the plot.
# The `print` functions runs also the `revolver_check_cohort` function which
# tells us that some patient have only 1 clone with drivers, and therefore they
# can just be expanded.
TRACERx_NEJM_2017_REVOLVER
## $patients
## [1] "CRUK0001" "CRUK0002" "CRUK0003" "CRUK0004" "CRUK0005" "CRUK0006"
## [7] "CRUK0007" "CRUK0008" "CRUK0009" "CRUK0010" "CRUK0011" "CRUK0012"
## [13] "CRUK0013" "CRUK0014" "CRUK0015" "CRUK0016" "CRUK0017" "CRUK0018"
## [19] "CRUK0019" "CRUK0020" "CRUK0021" "CRUK0022" "CRUK0023" "CRUK0024"
## [25] "CRUK0025" "CRUK0026" "CRUK0027" "CRUK0028" "CRUK0029" "CRUK0030"
## [31] "CRUK0031" "CRUK0032" "CRUK0033" "CRUK0034" "CRUK0035" "CRUK0036"
## [37] "CRUK0037" "CRUK0038" "CRUK0039" "CRUK0040" "CRUK0041" "CRUK0042"
## [43] "CRUK0043" "CRUK0044" "CRUK0045" "CRUK0046" "CRUK0047" "CRUK0048"
## [49] "CRUK0049" "CRUK0050" "CRUK0051" "CRUK0052" "CRUK0054" "CRUK0055"
## [55] "CRUK0056" "CRUK0057" "CRUK0058" "CRUK0059" "CRUK0060" "CRUK0061"
## [61] "CRUK0062" "CRUK0063" "CRUK0064" "CRUK0065" "CRUK0066" "CRUK0067"
## [67] "CRUK0068" "CRUK0069" "CRUK0070" "CRUK0071" "CRUK0072" "CRUK0073"
## [73] "CRUK0074" "CRUK0075" "CRUK0076" "CRUK0077" "CRUK0078" "CRUK0079"
## [79] "CRUK0080" "CRUK0081" "CRUK0082" "CRUK0083" "CRUK0084" "CRUK0085"
## [85] "CRUK0086" "CRUK0087" "CRUK0088" "CRUK0089" "CRUK0090" "CRUK0091"
## [91] "CRUK0092" "CRUK0093" "CRUK0094" "CRUK0095" "CRUK0096" "CRUK0097"
## [97] "CRUK0098" "CRUK0099" "CRUK0100"
##
## $variantIDs
## [1] "NF1" "ARHGAP35" "TP53" "MGA" "WRN"
## [6] "EGFR" "PASK" "RB1" "IKZF1" "KRAS"
## [11] "MET" "TERT" "EP300" "PIK3CA" "CDKN2A"
## [16] "CTNNB1" "SMAD4" "NOTCH1" "NRAS" "CMTR2"
## [21] "BRAF" "PLXNB2" "KEAP1" "MAP3K1" "FANCC"
## [26] "SGK223" "STK11" "PRDM1" "U2AF1" "MYC"
## [31] "ARID2" "KMT2C" "NFE2L2" "SETD2" "FLT4"
## [36] "RNF43" "BAP1" "FAT1" "SPEN" "CBLB"
## [41] "ASXL1" "PTPRC" "DNM2" "LATS1" "ARID1B"
## [46] "COL5A2" "COL2A1" "PRF1" "NCOR1" "CHEK2"
## [51] "CIC" "KMT2D" "POLE" "ATM" "SERPINB13"
## [56] "APC" "CCND1" "TSC2" "FBXW7" "FGFR1"
## [61] "RAD21" "FAS" "NCOA6" "CREBBP" "PHOX2B"
## [66] "GATA3" "NOTCH2" "UBR5" "FANCM" "RASA1"
## [71] "SMARCA4" "SOX2" "CYLD" "MLH1" "PDGFRA"
## [76] "PTEN" "DICER1" "WT1" "CUX1"
##
## $variantIDs.driver
## [1] "NF1" "ARHGAP35" "TP53" "MGA" "WRN"
## [6] "EGFR" "PASK" "RB1" "IKZF1" "KRAS"
## [11] "MET" "TERT" "EP300" "PIK3CA" "CDKN2A"
## [16] "CTNNB1" "SMAD4" "NOTCH1" "NRAS" "CMTR2"
## [21] "BRAF" "PLXNB2" "KEAP1" "MAP3K1" "FANCC"
## [26] "SGK223" "STK11" "PRDM1" "U2AF1" "MYC"
## [31] "ARID2" "KMT2C" "NFE2L2" "SETD2" "FLT4"
## [36] "RNF43" "BAP1" "FAT1" "SPEN" "CBLB"
## [41] "ASXL1" "PTPRC" "DNM2" "LATS1" "ARID1B"
## [46] "COL5A2" "COL2A1" "PRF1" "NCOR1" "CHEK2"
## [51] "CIC" "KMT2D" "POLE" "ATM" "SERPINB13"
## [56] "APC" "CCND1" "TSC2" "FBXW7" "FGFR1"
## [61] "RAD21" "FAS" "NCOA6" "CREBBP" "PHOX2B"
## [66] "GATA3" "NOTCH2" "UBR5" "FANCM" "RASA1"
## [71] "SMARCA4" "SOX2" "CYLD" "MLH1" "PDGFRA"
## [76] "PTEN" "DICER1" "WT1" "CUX1"
##
## $numVariants
## [1] 450
##
## $annotation
## [1] "TRACERx NEJM 2017"
##
## $dataset
## $dataset$CRUK0001
## # A tibble: 7 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0001 NF1 TRUE FALSE 1 1
## 2 __mu… CRUK… CRUK0001 ARHGAP35 TRUE FALSE 2 1
## 3 __mu… CRUK… CRUK0001 TP53 TRUE TRUE 3 4
## 4 __mu… CRUK… CRUK0001 MGA TRUE TRUE 3 4
## 5 __mu… CRUK… CRUK0001 WRN TRUE TRUE 3 4
## 6 __mu… Anno… CRUK0001 EGFR TRUE TRUE 3 4
## 7 __mu… CRUK… CRUK0001 PASK TRUE FALSE 5 1
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>
##
## $dataset$CRUK0002
## # A tibble: 7 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0002 RB1 TRUE FALSE 1 3
## 2 __mu… CRUK… CRUK0002 IKZF1 TRUE FALSE 1 3
## 3 __mu… Anno… CRUK0002 KRAS TRUE FALSE 1 3
## 4 __mu… CRUK… CRUK0002 MET TRUE TRUE 2 2
## 5 __mu… Anno… CRUK0002 TERT TRUE TRUE 2 2
## 6 __mu… CRUK… CRUK0002 NF1 TRUE FALSE 5 1
## 7 __mu… CRUK… CRUK0002 EP300 TRUE FALSE 6 1
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>
##
## $dataset$CRUK0003
## # A tibble: 4 x 14
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0003 PIK3CA TRUE TRUE 1 3
## 2 __mu… CRUK… CRUK0003 EGFR TRUE TRUE 1 3
## 3 __mu… Anno… CRUK0003 CDKN2A TRUE TRUE 1 3
## 4 __mu… CRUK… CRUK0003 CTNNB1 TRUE FALSE 4 1
## # … with 6 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>, R6 <dbl>
##
## $dataset$CRUK0004
## # A tibble: 4 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0004 SMAD4 TRUE FALSE 1 2
## 2 __mu… CRUK… CRUK0004 NOTCH1 TRUE FALSE 1 2
## 3 __mu… CRUK… CRUK0004 TP53 TRUE TRUE 2 2
## 4 __mu… CRUK… CRUK0004 EGFR TRUE TRUE 2 2
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>
##
## $dataset$CRUK0005
## # A tibble: 6 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0005 NRAS TRUE FALSE 1 1
## 2 __mu… CRUK… CRUK0005 CMTR2 TRUE TRUE 2 5
## 3 __mu… CRUK… CRUK0005 TP53 TRUE TRUE 2 5
## 4 __mu… CRUK… CRUK0005 BRAF TRUE TRUE 2 5
## 5 __mu… CRUK… CRUK0005 PASK TRUE TRUE 2 5
## 6 __mu… Anno… CRUK0005 TERT TRUE TRUE 2 5
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>
##
## $dataset$CRUK0006
## # A tibble: 6 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0006 PLXNB2 TRUE TRUE 1 4
## 2 __mu… CRUK… CRUK0006 TP53 TRUE TRUE 1 4
## 3 __mu… CRUK… CRUK0006 KEAP1 TRUE TRUE 1 4
## 4 __mu… Anno… CRUK0006 TERT TRUE TRUE 1 4
## 5 __mu… CRUK… CRUK0006 MAP3K1 TRUE FALSE 2 1
## 6 __mu… CRUK… CRUK0006 FANCC TRUE FALSE 7 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0007
## # A tibble: 3 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0007 PIK3CA TRUE TRUE 1 3
## 2 __mu… CRUK… CRUK0007 EGFR TRUE TRUE 1 3
## 3 __mu… Anno… CRUK0007 SGK223 TRUE TRUE 1 3
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0008
## # A tibble: 6 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0008 KEAP1 TRUE TRUE 2 5
## 2 __mu… CRUK… CRUK0008 STK11 TRUE TRUE 2 5
## 3 __mu… CRUK… CRUK0008 PRDM1 TRUE TRUE 2 5
## 4 __mu… CRUK… CRUK0008 U2AF1 TRUE TRUE 2 5
## 5 __mu… Anno… CRUK0008 MYC TRUE TRUE 2 5
## 6 __mu… CRUK… CRUK0008 ARID2 TRUE FALSE 3 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0009
## # A tibble: 7 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0009 BRAF TRUE TRUE 1 6
## 2 __mu… CRUK… CRUK0009 TP53 TRUE TRUE 1 6
## 3 __mu… CRUK… CRUK0009 ARHGAP35 TRUE TRUE 1 6
## 4 __mu… CRUK… CRUK0009 KMT2C TRUE TRUE 1 6
## 5 __mu… Anno… CRUK0009 NFE2L2 TRUE TRUE 1 6
## 6 __mu… Anno… CRUK0009 MET TRUE TRUE 1 6
## 7 __mu… Anno… CRUK0009 TERT TRUE FALSE 2 1
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>
##
## $dataset$CRUK0010
## # A tibble: 3 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0010 SETD2 TRUE TRUE 1 3
## 2 __mu… CRUK… CRUK0010 EGFR TRUE TRUE 1 3
## 3 __mu… Anno… CRUK0010 TERT TRUE TRUE 1 3
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0011
## # A tibble: 2 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0011 KRAS TRUE TRUE 1 1
## 2 __mu… CRUK… CRUK0011 FLT4 TRUE FALSE 3 1
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>
##
## $dataset$CRUK0012
## # A tibble: 1 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0012 EGFR TRUE TRUE 1 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0013
## # A tibble: 4 x 14
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0013 STK11 TRUE TRUE 1 1
## 2 __mu… CRUK… CRUK0013 NOTCH1 TRUE FALSE 2 1
## 3 __mu… Anno… CRUK0013 KRAS TRUE FALSE 3 1
## 4 __mu… Anno… CRUK0013 EGFR TRUE FALSE 4 1
## # … with 6 more variables: CCF <chr>, LN1 <dbl>, LN2 <dbl>, R1 <dbl>,
## # R2 <dbl>, R3 <dbl>
##
## $dataset$CRUK0014
## # A tibble: 3 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0014 TP53 TRUE TRUE 1 2
## 2 __mu… CRUK… CRUK0014 KRAS TRUE TRUE 1 2
## 3 __mu… CRUK… CRUK0014 RNF43 TRUE FALSE 2 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0015
## # A tibble: 4 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0015 BAP1 TRUE TRUE 1 2
## 2 __mu… CRUK… CRUK0015 EGFR TRUE TRUE 1 2
## 3 __mu… CRUK… CRUK0015 TP53 TRUE FALSE 2 1
## 4 __mu… CRUK… CRUK0015 RB1 TRUE FALSE 3 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0016
## # A tibble: 11 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0016 TP53 TRUE TRUE 1 6
## 2 __mu… CRUK… CRUK0016 FAT1 TRUE TRUE 1 6
## 3 __mu… CRUK… CRUK0016 SPEN TRUE TRUE 1 6
## 4 __mu… CRUK… CRUK0016 CBLB TRUE TRUE 1 6
## 5 __mu… Anno… CRUK0016 TERT TRUE TRUE 1 6
## 6 __mu… Anno… CRUK0016 CDKN2A TRUE TRUE 1 6
## 7 __mu… CRUK… CRUK0016 ASXL1 TRUE FALSE 2 1
## 8 __mu… CRUK… CRUK0016 PTPRC TRUE FALSE 6 1
## 9 __mu… CRUK… CRUK0016 DNM2 TRUE FALSE 10 1
## 10 __mu… CRUK… CRUK0016 LATS1 TRUE FALSE 16 2
## 11 __mu… CRUK… CRUK0016 ARID1B TRUE FALSE 16 2
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0017
## # A tibble: 6 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0017 TP53 TRUE TRUE 1 5
## 2 __mu… CRUK… CRUK0017 ARID1B TRUE TRUE 1 5
## 3 __mu… CRUK… CRUK0017 ARID2 TRUE TRUE 1 5
## 4 __mu… CRUK… CRUK0017 KEAP1 TRUE TRUE 1 5
## 5 __mu… Anno… CRUK0017 MYC TRUE TRUE 1 5
## 6 __mu… CRUK… CRUK0017 KRAS TRUE FALSE 3 1
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>
##
## $dataset$CRUK0018
## # A tibble: 4 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0018 CMTR2 TRUE TRUE 1 4
## 2 __mu… CRUK… CRUK0018 KRAS TRUE TRUE 1 4
## 3 __mu… CRUK… CRUK0018 MGA TRUE TRUE 1 4
## 4 __mu… CRUK… CRUK0018 COL5A2 TRUE TRUE 1 4
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>
##
## $dataset$CRUK0019
## # A tibble: 1 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0019 EGFR TRUE TRUE 1 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0020
## # A tibble: 10 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0020 KEAP1 TRUE TRUE 1 7
## 2 __mu… CRUK… CRUK0020 TP53 TRUE TRUE 1 7
## 3 __mu… CRUK… CRUK0020 MGA TRUE TRUE 1 7
## 4 __mu… CRUK… CRUK0020 ARID2 TRUE TRUE 1 7
## 5 __mu… CRUK… CRUK0020 COL2A1 TRUE TRUE 1 7
## 6 __mu… CRUK… CRUK0020 PRF1 TRUE TRUE 1 7
## 7 __mu… Anno… CRUK0020 KRAS TRUE TRUE 1 7
## 8 __mu… CRUK… CRUK0020 PIK3CA TRUE FALSE 2 1
## 9 __mu… CRUK… CRUK0020 BAP1 TRUE FALSE 3 1
## 10 __mu… CRUK… CRUK0020 NCOR1 TRUE FALSE 4 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0021
## # A tibble: 4 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0021 EGFR TRUE TRUE 1 4
## 2 __mu… CRUK… CRUK0021 TP53 TRUE TRUE 1 4
## 3 __mu… CRUK… CRUK0021 CHEK2 TRUE TRUE 1 4
## 4 __mu… Anno… CRUK0021 CDKN2A TRUE TRUE 1 4
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0022
## # A tibble: 3 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0022 TP53 TRUE TRUE 1 2
## 2 __mu… CRUK… CRUK0022 EGFR TRUE TRUE 1 2
## 3 __mu… CRUK… CRUK0022 CIC TRUE FALSE 2 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0023
## # A tibble: 6 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0023 WRN TRUE TRUE 1 3
## 2 __mu… CRUK… CRUK0023 KRAS TRUE TRUE 1 3
## 3 __mu… Anno… CRUK0023 CDKN2A TRUE TRUE 1 3
## 4 __mu… CRUK… CRUK0023 TP53 TRUE FALSE 2 1
## 5 __mu… CRUK… CRUK0023 PTPRC TRUE FALSE 4 2
## 6 __mu… CRUK… CRUK0023 KMT2D TRUE FALSE 4 2
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>
##
## $dataset$CRUK0024
## # A tibble: 6 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0024 TP53 TRUE TRUE 1 4
## 2 __mu… CRUK… CRUK0024 STK11 TRUE TRUE 1 4
## 3 __mu… CRUK… CRUK0024 POLE TRUE TRUE 1 4
## 4 __mu… Anno… CRUK0024 EGFR TRUE TRUE 1 4
## 5 __mu… CRUK… CRUK0024 ATM TRUE FALSE 3 1
## 6 __mu… CRUK… CRUK0024 NCOR1 TRUE FALSE 4 1
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R3 <dbl>, R4 <dbl>,
## # R6 <dbl>
##
## $dataset$CRUK0025
## # A tibble: 3 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0025 KRAS TRUE TRUE 1 3
## 2 __mu… CRUK… CRUK0025 TP53 TRUE TRUE 1 3
## 3 __mu… CRUK… CRUK0025 MGA TRUE TRUE 1 3
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>
##
## $dataset$CRUK0026
## # A tibble: 4 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0026 TP53 TRUE TRUE 1 4
## 2 __mu… CRUK… CRUK0026 EGFR TRUE TRUE 1 4
## 3 __mu… CRUK… CRUK0026 RB1 TRUE TRUE 1 4
## 4 __mu… CRUK… CRUK0026 SERPINB13 TRUE TRUE 1 4
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0027
## # A tibble: 3 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0027 KRAS TRUE TRUE 1 2
## 2 __mu… CRUK… CRUK0027 TP53 TRUE TRUE 1 2
## 3 __mu… CRUK… CRUK0027 PLXNB2 TRUE FALSE 2 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0028
## # A tibble: 2 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0028 APC TRUE TRUE 1 2
## 2 __mu… Anno… CRUK0028 EGFR TRUE TRUE 1 2
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0029
## # A tibble: 4 x 15
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0029 TP53 TRUE TRUE 1 4
## 2 __mu… CRUK… CRUK0029 NRAS TRUE TRUE 1 4
## 3 __mu… CRUK… CRUK0029 MGA TRUE TRUE 1 4
## 4 __mu… Anno… CRUK0029 CCND1 TRUE TRUE 1 4
## # … with 7 more variables: CCF <chr>, R2 <dbl>, R4 <dbl>, R5 <dbl>,
## # R6 <dbl>, R7 <dbl>, R8 <dbl>
##
## $dataset$CRUK0030
## # A tibble: 6 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0030 KRAS TRUE TRUE 1 6
## 2 __mu… CRUK… CRUK0030 TSC2 TRUE TRUE 1 6
## 3 __mu… CRUK… CRUK0030 U2AF1 TRUE TRUE 1 6
## 4 __mu… CRUK… CRUK0030 TP53 TRUE TRUE 1 6
## 5 __mu… CRUK… CRUK0030 FBXW7 TRUE TRUE 1 6
## 6 __mu… CRUK… CRUK0030 NF1 TRUE TRUE 1 6
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>
##
## $dataset$CRUK0031
## # A tibble: 5 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0031 KEAP1 TRUE TRUE 1 4
## 2 __mu… CRUK… CRUK0031 CDKN2A TRUE TRUE 1 4
## 3 __mu… CRUK… CRUK0031 PRF1 TRUE TRUE 1 4
## 4 __mu… Anno… CRUK0031 FGFR1 TRUE TRUE 1 4
## 5 __mu… CRUK… CRUK0031 NF1 TRUE FALSE 6 1
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>
##
## $dataset$CRUK0032
## # A tibble: 6 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0032 ATM TRUE TRUE 1 4
## 2 __mu… CRUK… CRUK0032 RAD21 TRUE TRUE 1 4
## 3 __mu… CRUK… CRUK0032 U2AF1 TRUE TRUE 1 4
## 4 __mu… CRUK… CRUK0032 RNF43 TRUE TRUE 1 4
## 5 __mu… Anno… CRUK0032 CCND1 TRUE FALSE 4 1
## 6 __mu… CRUK… CRUK0032 ARID1B TRUE FALSE 6 1
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>
##
## $dataset$CRUK0033
## # A tibble: 2 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0033 KEAP1 TRUE TRUE 1 2
## 2 __mu… CRUK… CRUK0033 CTNNB1 TRUE TRUE 1 2
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0034
## # A tibble: 4 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0034 ATM TRUE TRUE 1 3
## 2 __mu… CRUK… CRUK0034 KRAS TRUE TRUE 1 3
## 3 __mu… CRUK… CRUK0034 PLXNB2 TRUE TRUE 1 3
## 4 __mu… CRUK… CRUK0034 MGA TRUE FALSE 4 1
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>
##
## $dataset$CRUK0035
## # A tibble: 3 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0035 TP53 TRUE TRUE 1 2
## 2 __mu… CRUK… CRUK0035 FAS TRUE TRUE 1 2
## 3 __mu… CRUK… CRUK0035 FLT4 TRUE FALSE 4 1
## # … with 5 more variables: CCF <chr>, LN1 <dbl>, R1 <dbl>, R2 <dbl>,
## # R3 <dbl>
##
## $dataset$CRUK0036
## # A tibble: 5 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0036 KRAS TRUE TRUE 1 5
## 2 __mu… CRUK… CRUK0036 PIK3CA TRUE TRUE 1 5
## 3 __mu… CRUK… CRUK0036 KEAP1 TRUE TRUE 1 5
## 4 __mu… CRUK… CRUK0036 ARHGAP35 TRUE TRUE 1 5
## 5 __mu… Anno… CRUK0036 TERT TRUE TRUE 1 5
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>
##
## $dataset$CRUK0037
## # A tibble: 3 x 14
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0037 NCOA6 TRUE TRUE 1 3
## 2 __mu… CRUK… CRUK0037 CREBBP TRUE TRUE 1 3
## 3 __mu… CRUK… CRUK0037 KRAS TRUE TRUE 1 3
## # … with 6 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>, R5 <dbl>
##
## $dataset$CRUK0038
## # A tibble: 2 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0038 KRAS TRUE TRUE 1 1
## 2 __mu… CRUK… CRUK0038 KMT2D TRUE FALSE 3 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0039
## # A tibble: 4 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0039 KRAS TRUE TRUE 1 4
## 2 __mu… CRUK… CRUK0039 CMTR2 TRUE TRUE 1 4
## 3 __mu… CRUK… CRUK0039 NF1 TRUE TRUE 1 4
## 4 __mu… CRUK… CRUK0039 PHOX2B TRUE TRUE 1 4
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>
##
## $dataset$CRUK0040
## # A tibble: 4 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0040 NCOR1 TRUE TRUE 1 4
## 2 __mu… CRUK… CRUK0040 RAD21 TRUE TRUE 1 4
## 3 __mu… CRUK… CRUK0040 KRAS TRUE TRUE 1 4
## 4 __mu… CRUK… CRUK0040 GATA3 TRUE TRUE 1 4
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0041
## # A tibble: 3 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0041 BRAF TRUE TRUE 1 3
## 2 __mu… Anno… CRUK0041 TERT TRUE TRUE 1 3
## 3 __mu… Anno… CRUK0041 EGFR TRUE TRUE 1 3
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>
##
## $dataset$CRUK0042
## # A tibble: 1 x 10
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0042 KRAS TRUE TRUE 1 1
## # … with 2 more variables: CCF <chr>, R1 <dbl>
##
## $dataset$CRUK0043
## # A tibble: 1 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0043 MET TRUE TRUE 1 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0044
## # A tibble: 1 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0044 KRAS TRUE TRUE 1 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0045
## # A tibble: 1 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0045 BAP1 TRUE TRUE 1 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R3 <dbl>
##
## $dataset$CRUK0046
## # A tibble: 2 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0046 KEAP1 TRUE TRUE 1 2
## 2 __mu… CRUK… CRUK0046 APC TRUE TRUE 1 2
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>
##
## $dataset$CRUK0047
## # A tibble: 4 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0047 STK11 TRUE TRUE 1 4
## 2 __mu… CRUK… CRUK0047 APC TRUE TRUE 1 4
## 3 __mu… CRUK… CRUK0047 KRAS TRUE TRUE 1 4
## 4 __mu… Anno… CRUK0047 MYC TRUE TRUE 1 4
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0048
## # A tibble: 7 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0048 APC TRUE TRUE 1 7
## 2 __mu… CRUK… CRUK0048 PRDM1 TRUE TRUE 1 7
## 3 __mu… CRUK… CRUK0048 ARHGAP35 TRUE TRUE 1 7
## 4 __mu… CRUK… CRUK0048 TP53 TRUE TRUE 1 7
## 5 __mu… CRUK… CRUK0048 BRAF TRUE TRUE 1 7
## 6 __mu… Anno… CRUK0048 EGFR TRUE TRUE 1 7
## 7 __mu… Anno… CRUK0048 MYC TRUE TRUE 1 7
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>
##
## $dataset$CRUK0049
## # A tibble: 5 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0049 RB1 TRUE TRUE 1 5
## 2 __mu… CRUK… CRUK0049 TP53 TRUE TRUE 1 5
## 3 __mu… CRUK… CRUK0049 COL2A1 TRUE TRUE 1 5
## 4 __mu… Anno… CRUK0049 EGFR TRUE TRUE 1 5
## 5 __mu… Anno… CRUK0049 KRAS TRUE TRUE 1 5
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0050
## # A tibble: 3 x 14
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0050 KRAS TRUE TRUE 1 3
## 2 __mu… CRUK… CRUK0050 STK11 TRUE TRUE 1 3
## 3 __mu… Anno… CRUK0050 MYC TRUE TRUE 1 3
## # … with 6 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>, R5 <dbl>
##
## $dataset$CRUK0051
## # A tibble: 5 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0051 KRAS TRUE TRUE 1 4
## 2 __mu… CRUK… CRUK0051 FBXW7 TRUE TRUE 1 4
## 3 __mu… CRUK… CRUK0051 TP53 TRUE TRUE 1 4
## 4 __mu… Anno… CRUK0051 EGFR TRUE TRUE 1 4
## 5 __mu… CRUK… CRUK0051 EP300 TRUE FALSE 3 1
## # … with 4 more variables: CCF <chr>, R2 <dbl>, R3 <dbl>, R4 <dbl>
##
## $dataset$CRUK0052
## # A tibble: 9 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0052 KMT2D TRUE TRUE 1 8
## 2 __mu… CRUK… CRUK0052 KRAS TRUE TRUE 1 8
## 3 __mu… CRUK… CRUK0052 NOTCH2 TRUE TRUE 1 8
## 4 __mu… CRUK… CRUK0052 MGA TRUE TRUE 1 8
## 5 __mu… CRUK… CRUK0052 KEAP1 TRUE TRUE 1 8
## 6 __mu… CRUK… CRUK0052 TP53 TRUE TRUE 1 8
## 7 __mu… CRUK… CRUK0052 NF1 TRUE TRUE 1 8
## 8 __mu… CRUK… CRUK0052 SGK223 TRUE TRUE 1 8
## 9 __mu… CRUK… CRUK0052 UBR5 TRUE FALSE 2 1
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R3 <dbl>, R4 <dbl>
##
## $dataset$CRUK0054
## # A tibble: 1 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0054 EGFR TRUE TRUE 1 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0055
## # A tibble: 3 x 10
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0055 FANCM TRUE TRUE 1 2
## 2 __mu… CRUK… CRUK0055 UBR5 TRUE TRUE 1 2
## 3 __mu… CRUK… CRUK0055 FAT1 TRUE FALSE 2 1
## # … with 2 more variables: CCF <chr>, R2 <dbl>
##
## $dataset$CRUK0056
## # A tibble: 3 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0056 RASA1 TRUE TRUE 1 2
## 2 __mu… CRUK… CRUK0056 CREBBP TRUE TRUE 1 2
## 3 __mu… CRUK… CRUK0056 TP53 TRUE FALSE 3 1
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>
##
## $dataset$CRUK0057
## # A tibble: 5 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0057 KRAS TRUE TRUE 1 5
## 2 __mu… CRUK… CRUK0057 SMARCA4 TRUE TRUE 1 5
## 3 __mu… CRUK… CRUK0057 TSC2 TRUE TRUE 1 5
## 4 __mu… CRUK… CRUK0057 DNM2 TRUE TRUE 1 5
## 5 __mu… Anno… CRUK0057 TERT TRUE TRUE 1 5
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0058
## # A tibble: 2 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0058 TP53 TRUE TRUE 1 2
## 2 __mu… CRUK… CRUK0058 EGFR TRUE TRUE 1 2
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0059
## # A tibble: 1 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0059 KRAS TRUE TRUE 1 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0060
## # A tibble: 11 x 10
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0060 SERPINB13 TRUE TRUE 1 11
## 2 __mu… CRUK… CRUK0060 ARID2 TRUE TRUE 1 11
## 3 __mu… CRUK… CRUK0060 COL5A2 TRUE TRUE 1 11
## 4 __mu… CRUK… CRUK0060 FANCM TRUE TRUE 1 11
## 5 __mu… CRUK… CRUK0060 PHOX2B TRUE TRUE 1 11
## 6 __mu… CRUK… CRUK0060 COL2A1 TRUE TRUE 1 11
## 7 __mu… CRUK… CRUK0060 RASA1 TRUE TRUE 1 11
## 8 __mu… CRUK… CRUK0060 NF1 TRUE TRUE 1 11
## 9 __mu… CRUK… CRUK0060 NCOA6 TRUE TRUE 1 11
## 10 __mu… CRUK… CRUK0060 NOTCH2 TRUE TRUE 1 11
## 11 __mu… CRUK… CRUK0060 KMT2C TRUE TRUE 1 11
## # … with 2 more variables: CCF <chr>, R1 <dbl>
##
## $dataset$CRUK0061
## # A tibble: 1 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0061 STK11 TRUE TRUE 1 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0062
## # A tibble: 7 x 16
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0062 FAS TRUE FALSE 1 1
## 2 __mu… CRUK… CRUK0062 PLXNB2 TRUE FALSE 2 1
## 3 __mu… CRUK… CRUK0062 TP53 TRUE TRUE 4 4
## 4 __mu… Anno… CRUK0062 PIK3CA TRUE TRUE 4 4
## 5 __mu… Anno… CRUK0062 SOX2 TRUE TRUE 4 4
## 6 __mu… Anno… CRUK0062 CCND1 TRUE TRUE 4 4
## 7 __mu… CRUK… CRUK0062 UBR5 TRUE FALSE 16 1
## # … with 8 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>, R5 <dbl>, R6 <dbl>, R7 <dbl>
##
## $dataset$CRUK0063
## # A tibble: 11 x 14
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0063 NF1 TRUE FALSE 1 2
## 2 __mu… CRUK… CRUK0063 CYLD TRUE FALSE 1 2
## 3 __mu… CRUK… CRUK0063 PIK3CA TRUE TRUE 2 7
## 4 __mu… CRUK… CRUK0063 TP53 TRUE TRUE 2 7
## 5 __mu… CRUK… CRUK0063 FBXW7 TRUE TRUE 2 7
## 6 __mu… CRUK… CRUK0063 CDKN2A TRUE TRUE 2 7
## 7 __mu… Anno… CRUK0063 SOX2 TRUE TRUE 2 7
## 8 __mu… Anno… CRUK0063 TERT TRUE TRUE 2 7
## 9 __mu… Anno… CRUK0063 PRF1 TRUE TRUE 2 7
## 10 __mu… CRUK… CRUK0063 FANCM TRUE FALSE 6 1
## 11 __mu… CRUK… CRUK0063 EP300 TRUE FALSE 10 1
## # … with 6 more variables: CCF <chr>, R3 <dbl>, R4 <dbl>, R5 <dbl>,
## # R6 <dbl>, R7 <dbl>
##
## $dataset$CRUK0064
## # A tibble: 3 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0064 TP53 TRUE TRUE 1 1
## 2 __mu… CRUK… CRUK0064 MLH1 TRUE FALSE 2 2
## 3 __mu… CRUK… CRUK0064 FAT1 TRUE FALSE 2 2
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0065
## # A tibble: 9 x 15
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0065 TP53 TRUE TRUE 1 4
## 2 __mu… CRUK… CRUK0065 NFE2L2 TRUE TRUE 1 4
## 3 __mu… Anno… CRUK0065 PIK3CA TRUE TRUE 1 4
## 4 __mu… Anno… CRUK0065 SOX2 TRUE TRUE 1 4
## 5 __mu… CRUK… CRUK0065 MLH1 TRUE FALSE 2 3
## 6 __mu… CRUK… CRUK0065 PTPRC TRUE FALSE 2 3
## 7 __mu… CRUK… CRUK0065 UBR5 TRUE FALSE 2 3
## 8 __mu… CRUK… CRUK0065 NOTCH1 TRUE FALSE 6 2
## 9 __mu… CRUK… CRUK0065 NCOA6 TRUE FALSE 6 2
## # … with 7 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>, R5 <dbl>, R6 <dbl>
##
## $dataset$CRUK0066
## # A tibble: 8 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0066 TP53 TRUE TRUE 1 7
## 2 __mu… CRUK… CRUK0066 NOTCH1 TRUE TRUE 1 7
## 3 __mu… CRUK… CRUK0066 CDKN2A TRUE TRUE 1 7
## 4 __mu… CRUK… CRUK0066 WRN TRUE TRUE 1 7
## 5 __mu… Anno… CRUK0066 PDGFRA TRUE TRUE 1 7
## 6 __mu… Anno… CRUK0066 TERT TRUE TRUE 1 7
## 7 __mu… Anno… CRUK0066 NCOA6 TRUE TRUE 1 7
## 8 __mu… CRUK… CRUK0066 COL5A2 TRUE FALSE 9 1
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>
##
## $dataset$CRUK0067
## # A tibble: 6 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0067 NOTCH1 TRUE TRUE 1 5
## 2 __mu… CRUK… CRUK0067 TP53 TRUE TRUE 1 5
## 3 __mu… Anno… CRUK0067 PIK3CA TRUE TRUE 1 5
## 4 __mu… Anno… CRUK0067 SOX2 TRUE TRUE 1 5
## 5 __mu… Anno… CRUK0067 CDKN2A TRUE TRUE 1 5
## 6 __mu… CRUK… CRUK0067 NFE2L2 TRUE FALSE 2 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R3 <dbl>
##
## $dataset$CRUK0068
## # A tibble: 8 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0068 TP53 TRUE TRUE 1 5
## 2 __mu… CRUK… CRUK0068 PTEN TRUE TRUE 1 5
## 3 __mu… CRUK… CRUK0068 KMT2D TRUE TRUE 1 5
## 4 __mu… Anno… CRUK0068 PIK3CA TRUE TRUE 1 5
## 5 __mu… Anno… CRUK0068 SOX2 TRUE TRUE 1 5
## 6 __mu… CRUK… CRUK0068 MGA TRUE FALSE 3 1
## 7 __mu… CRUK… CRUK0068 SETD2 TRUE FALSE 4 1
## 8 __mu… Anno… CRUK0068 TERT TRUE FALSE 9 1
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>
##
## $dataset$CRUK0069
## # A tibble: 5 x 14
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0069 TP53 TRUE TRUE 1 4
## 2 __mu… CRUK… CRUK0069 FAT1 TRUE TRUE 1 4
## 3 __mu… Anno… CRUK0069 PDGFRA TRUE TRUE 1 4
## 4 __mu… Anno… CRUK0069 FGFR1 TRUE TRUE 1 4
## 5 __mu… CRUK… CRUK0069 KRAS TRUE FALSE 13 1
## # … with 6 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>, R5 <dbl>
##
## $dataset$CRUK0070
## # A tibble: 6 x 14
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0070 DNM2 TRUE TRUE 1 4
## 2 __mu… CRUK… CRUK0070 TP53 TRUE TRUE 1 4
## 3 __mu… Anno… CRUK0070 COL5A2 TRUE TRUE 1 4
## 4 __mu… Anno… CRUK0070 SOX2 TRUE TRUE 1 4
## 5 __mu… CRUK… CRUK0070 CBLB TRUE FALSE 2 1
## 6 __mu… Anno… CRUK0070 NFE2L2 TRUE FALSE 3 1
## # … with 6 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R4 <dbl>,
## # R6 <dbl>, R7 <dbl>
##
## $dataset$CRUK0071
## # A tibble: 4 x 15
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0071 CMTR2 TRUE TRUE 1 3
## 2 __mu… Anno… CRUK0071 PIK3CA TRUE TRUE 1 3
## 3 __mu… Anno… CRUK0071 SOX2 TRUE TRUE 1 3
## 4 __mu… CRUK… CRUK0071 UBR5 TRUE FALSE 4 1
## # … with 7 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R5 <dbl>, R6 <dbl>, R7 <dbl>
##
## $dataset$CRUK0072
## # A tibble: 6 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0072 TP53 TRUE TRUE 1 6
## 2 __mu… CRUK… CRUK0072 NFE2L2 TRUE TRUE 1 6
## 3 __mu… Anno… CRUK0072 PIK3CA TRUE TRUE 1 6
## 4 __mu… Anno… CRUK0072 SOX2 TRUE TRUE 1 6
## 5 __mu… Anno… CRUK0072 EGFR TRUE TRUE 1 6
## 6 __mu… Anno… CRUK0072 MYC TRUE TRUE 1 6
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R4 <dbl>
##
## $dataset$CRUK0073
## # A tibble: 9 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0073 CDKN2A TRUE TRUE 1 8
## 2 __mu… CRUK… CRUK0073 DICER1 TRUE TRUE 1 8
## 3 __mu… CRUK… CRUK0073 NFE2L2 TRUE TRUE 1 8
## 4 __mu… CRUK… CRUK0073 FAT1 TRUE TRUE 1 8
## 5 __mu… CRUK… CRUK0073 KMT2D TRUE TRUE 1 8
## 6 __mu… CRUK… CRUK0073 NOTCH2 TRUE TRUE 1 8
## 7 __mu… Anno… CRUK0073 FGFR1 TRUE TRUE 1 8
## 8 __mu… Anno… CRUK0073 MYC TRUE TRUE 1 8
## 9 __mu… CRUK… CRUK0073 PLXNB2 TRUE FALSE 2 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0074
## # A tibble: 6 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0074 TP53 TRUE TRUE 1 5
## 2 __mu… CRUK… CRUK0074 NFE2L2 TRUE TRUE 1 5
## 3 __mu… Anno… CRUK0074 PIK3CA TRUE TRUE 1 5
## 4 __mu… Anno… CRUK0074 SOX2 TRUE TRUE 1 5
## 5 __mu… Anno… CRUK0074 CCND1 TRUE TRUE 1 5
## 6 __mu… CRUK… CRUK0074 UBR5 TRUE FALSE 3 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0075
## # A tibble: 8 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0075 NOTCH1 TRUE TRUE 1 7
## 2 __mu… CRUK… CRUK0075 RASA1 TRUE TRUE 1 7
## 3 __mu… CRUK… CRUK0075 TP53 TRUE TRUE 1 7
## 4 __mu… CRUK… CRUK0075 FAT1 TRUE TRUE 1 7
## 5 __mu… CRUK… CRUK0075 MGA TRUE TRUE 1 7
## 6 __mu… CRUK… CRUK0075 PIK3CA TRUE TRUE 1 7
## 7 __mu… Anno… CRUK0075 FGFR1 TRUE TRUE 1 7
## 8 __mu… CRUK… CRUK0075 NFE2L2 TRUE FALSE 2 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0076
## # A tibble: 8 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0076 SERPINB13 TRUE TRUE 1 6
## 2 __mu… CRUK… CRUK0076 TP53 TRUE TRUE 1 6
## 3 __mu… CRUK… CRUK0076 ARID1B TRUE TRUE 1 6
## 4 __mu… Anno… CRUK0076 PIK3CA TRUE TRUE 1 6
## 5 __mu… Anno… CRUK0076 SOX2 TRUE TRUE 1 6
## 6 __mu… Anno… CRUK0076 FGFR1 TRUE TRUE 1 6
## 7 __mu… CRUK… CRUK0076 NCOR1 TRUE FALSE 2 1
## 8 __mu… CRUK… CRUK0076 COL5A2 TRUE FALSE 3 1
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>
##
## $dataset$CRUK0077
## # A tibble: 3 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0077 TP53 TRUE TRUE 1 3
## 2 __mu… CRUK… CRUK0077 LATS1 TRUE TRUE 1 3
## 3 __mu… CRUK… CRUK0077 KEAP1 TRUE TRUE 1 3
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>
##
## $dataset$CRUK0078
## # A tibble: 5 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0078 PLXNB2 TRUE TRUE 1 5
## 2 __mu… CRUK… CRUK0078 PTEN TRUE TRUE 1 5
## 3 __mu… Anno… CRUK0078 PIK3CA TRUE TRUE 1 5
## 4 __mu… Anno… CRUK0078 SOX2 TRUE TRUE 1 5
## 5 __mu… Anno… CRUK0078 FGFR1 TRUE TRUE 1 5
## # … with 4 more variables: CCF <chr>, R2 <dbl>, R3 <dbl>, R4 <dbl>
##
## $dataset$CRUK0079
## # A tibble: 6 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0079 FAT1 TRUE TRUE 1 6
## 2 __mu… CRUK… CRUK0079 TP53 TRUE TRUE 1 6
## 3 __mu… CRUK… CRUK0079 POLE TRUE TRUE 1 6
## 4 __mu… Anno… CRUK0079 PIK3CA TRUE TRUE 1 6
## 5 __mu… Anno… CRUK0079 SOX2 TRUE TRUE 1 6
## 6 __mu… Anno… CRUK0079 FGFR1 TRUE TRUE 1 6
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>
##
## $dataset$CRUK0080
## # A tibble: 5 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0080 TP53 TRUE TRUE 1 4
## 2 __mu… CRUK… CRUK0080 WT1 TRUE TRUE 1 4
## 3 __mu… Anno… CRUK0080 EGFR TRUE TRUE 1 4
## 4 __mu… Anno… CRUK0080 CCND1 TRUE TRUE 1 4
## 5 __mu… CRUK… CRUK0080 IKZF1 TRUE FALSE 3 1
## # … with 5 more variables: CCF <chr>, R3 <dbl>, R4 <dbl>, R5 <dbl>,
## # R6 <dbl>
##
## $dataset$CRUK0081
## # A tibble: 6 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0081 NOTCH1 TRUE TRUE 1 5
## 2 __mu… CRUK… CRUK0081 TP53 TRUE TRUE 1 5
## 3 __mu… CRUK… CRUK0081 CDKN2A TRUE TRUE 1 5
## 4 __mu… CRUK… CRUK0081 FAT1 TRUE TRUE 1 5
## 5 __mu… CRUK… CRUK0081 FANCC TRUE TRUE 1 5
## 6 __mu… CRUK… CRUK0081 CYLD TRUE FALSE 3 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R5 <dbl>
##
## $dataset$CRUK0082
## # A tibble: 8 x 14
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0082 TP53 TRUE TRUE 1 8
## 2 __mu… CRUK… CRUK0082 WT1 TRUE TRUE 1 8
## 3 __mu… CRUK… CRUK0082 PTEN TRUE TRUE 1 8
## 4 __mu… CRUK… CRUK0082 COL5A2 TRUE TRUE 1 8
## 5 __mu… CRUK… CRUK0082 KMT2D TRUE TRUE 1 8
## 6 __mu… Anno… CRUK0082 PIK3CA TRUE TRUE 1 8
## 7 __mu… Anno… CRUK0082 SOX2 TRUE TRUE 1 8
## 8 __mu… Anno… CRUK0082 FGFR1 TRUE TRUE 1 8
## # … with 6 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>, R5 <dbl>
##
## $dataset$CRUK0083
## # A tibble: 7 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0083 TP53 TRUE TRUE 1 7
## 2 __mu… CRUK… CRUK0083 FBXW7 TRUE TRUE 1 7
## 3 __mu… CRUK… CRUK0083 RASA1 TRUE TRUE 1 7
## 4 __mu… Anno… CRUK0083 PIK3CA TRUE TRUE 1 7
## 5 __mu… Anno… CRUK0083 SOX2 TRUE TRUE 1 7
## 6 __mu… Anno… CRUK0083 FGFR1 TRUE TRUE 1 7
## 7 __mu… Anno… CRUK0083 MYC TRUE TRUE 1 7
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>
##
## $dataset$CRUK0084
## # A tibble: 1 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0084 CREBBP TRUE TRUE 1 1
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>
##
## $dataset$CRUK0085
## # A tibble: 4 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0085 CHEK2 TRUE TRUE 1 4
## 2 __mu… CRUK… CRUK0085 CREBBP TRUE TRUE 1 4
## 3 __mu… CRUK… CRUK0085 LATS1 TRUE TRUE 1 4
## 4 __mu… CRUK… CRUK0085 FANCM TRUE TRUE 1 4
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>
##
## $dataset$CRUK0086
## # A tibble: 3 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0086 TP53 TRUE TRUE 1 3
## 2 __mu… CRUK… CRUK0086 ARID2 TRUE TRUE 1 3
## 3 __mu… Anno… CRUK0086 FAT1 TRUE TRUE 1 3
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R4 <dbl>
##
## $dataset$CRUK0087
## # A tibble: 4 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0087 NFE2L2 TRUE TRUE 1 4
## 2 __mu… CRUK… CRUK0087 TP53 TRUE TRUE 1 4
## 3 __mu… CRUK… CRUK0087 ASXL1 TRUE TRUE 1 4
## 4 __mu… CRUK… CRUK0087 PIK3CA TRUE TRUE 1 4
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>
##
## $dataset$CRUK0088
## # A tibble: 2 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0088 CUX1 TRUE TRUE 1 2
## 2 __mu… CRUK… CRUK0088 TP53 TRUE TRUE 1 2
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0089
## # A tibble: 3 x 10
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0089 PIK3CA TRUE TRUE 1 3
## 2 __mu… CRUK… CRUK0089 SMAD4 TRUE TRUE 1 3
## 3 __mu… CRUK… CRUK0089 KEAP1 TRUE TRUE 1 3
## # … with 2 more variables: CCF <chr>, R2 <dbl>
##
## $dataset$CRUK0090
## # A tibble: 5 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0090 CDKN2A TRUE TRUE 1 5
## 2 __mu… CRUK… CRUK0090 NCOA6 TRUE TRUE 1 5
## 3 __mu… CRUK… CRUK0090 CUX1 TRUE TRUE 1 5
## 4 __mu… CRUK… CRUK0090 COL2A1 TRUE TRUE 1 5
## 5 __mu… CRUK… CRUK0090 NRAS TRUE TRUE 1 5
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0091
## # A tibble: 3 x 10
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0091 TP53 TRUE TRUE 1 3
## 2 __mu… CRUK… CRUK0091 SMARCA4 TRUE TRUE 1 3
## 3 __mu… CRUK… CRUK0091 CDKN2A TRUE TRUE 1 3
## # … with 2 more variables: CCF <chr>, R2 <dbl>
##
## $dataset$CRUK0092
## # A tibble: 5 x 10
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0092 TP53 TRUE TRUE 1 5
## 2 __mu… CRUK… CRUK0092 SMAD4 TRUE TRUE 1 5
## 3 __mu… CRUK… CRUK0092 RASA1 TRUE TRUE 1 5
## 4 __mu… CRUK… CRUK0092 CBLB TRUE TRUE 1 5
## 5 __mu… CRUK… CRUK0092 PIK3CA TRUE TRUE 1 5
## # … with 2 more variables: CCF <chr>, R1 <dbl>
##
## $dataset$CRUK0093
## # A tibble: 7 x 10
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0093 DICER1 TRUE TRUE 1 7
## 2 __mu… CRUK… CRUK0093 CDKN2A TRUE TRUE 1 7
## 3 __mu… CRUK… CRUK0093 COL2A1 TRUE TRUE 1 7
## 4 __mu… CRUK… CRUK0093 GATA3 TRUE TRUE 1 7
## 5 __mu… CRUK… CRUK0093 CIC TRUE TRUE 1 7
## 6 __mu… CRUK… CRUK0093 COL5A2 TRUE TRUE 1 7
## 7 __mu… CRUK… CRUK0093 TP53 TRUE TRUE 1 7
## # … with 2 more variables: CCF <chr>, R1 <dbl>
##
## $dataset$CRUK0094
## # A tibble: 2 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0094 SMARCA4 TRUE TRUE 1 2
## 2 __mu… Anno… CRUK0094 TERT TRUE TRUE 1 2
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>
##
## $dataset$CRUK0095
## # A tibble: 3 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0095 TP53 TRUE TRUE 1 3
## 2 __mu… CRUK… CRUK0095 NF1 TRUE TRUE 1 3
## 3 __mu… CRUK… CRUK0095 RASA1 TRUE TRUE 1 3
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>
##
## $dataset$CRUK0096
## # A tibble: 3 x 16
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0096 KRAS TRUE TRUE 1 3
## 2 __mu… CRUK… CRUK0096 SGK223 TRUE TRUE 1 3
## 3 __mu… CRUK… CRUK0096 MAP3K1 TRUE TRUE 1 3
## # … with 8 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>, R5 <dbl>, R6 <dbl>, R7 <dbl>
##
## $dataset$CRUK0097
## # A tibble: 2 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0097 TP53 TRUE TRUE 1 2
## 2 __mu… CRUK… CRUK0097 PTEN TRUE TRUE 1 2
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0098
## # A tibble: 3 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0098 TP53 TRUE TRUE 1 2
## 2 __mu… Anno… CRUK0098 PTEN TRUE TRUE 1 2
## 3 __mu… CRUK… CRUK0098 UBR5 TRUE FALSE 3 1
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>
##
## $dataset$CRUK0099
## # A tibble: 3 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0099 STK11 TRUE TRUE 1 3
## 2 __mu… CRUK… CRUK0099 KEAP1 TRUE TRUE 1 3
## 3 __mu… CRUK… CRUK0099 TP53 TRUE TRUE 1 3
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R3 <dbl>, R6 <dbl>,
## # R7 <dbl>
##
## $dataset$CRUK0100
## # A tibble: 6 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0100 TP53 TRUE TRUE 1 6
## 2 __mu… CRUK… CRUK0100 PHOX2B TRUE TRUE 1 6
## 3 __mu… CRUK… CRUK0100 COL5A2 TRUE TRUE 1 6
## 4 __mu… CRUK… CRUK0100 STK11 TRUE TRUE 1 6
## 5 __mu… CRUK… CRUK0100 SPEN TRUE TRUE 1 6
## 6 __mu… Anno… CRUK0100 CDKN2A TRUE TRUE 1 6
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>
##
##
## $CCF
## $CCF$CRUK0001
## # A tibble: 4 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 3 4 TRUE TRUE 0.99 0.99 1
## 2 1 1 TRUE FALSE 0.86 0 0
## 3 2 1 TRUE FALSE 0.19 0 0.95
## 4 5 1 TRUE FALSE 0.82 0 0.71
##
## $CCF$CRUK0002
## # A tibble: 4 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE FALSE 0 0.92 0
## 2 2 2 TRUE TRUE 0.99 0.98 0.99
## 3 5 1 TRUE FALSE 0.78 0 0
## 4 6 1 TRUE FALSE 0.96 0.03 0.98
##
## $CCF$CRUK0003
## # A tibble: 2 x 9
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R6
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.98 0.97 0.87 0.97 0.99
## 2 4 1 TRUE FALSE 0 0 0.49 0 0.01
##
## $CCF$CRUK0004
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 2 TRUE FALSE 0 0 0.95 0.01
## 2 2 2 TRUE TRUE 0.99 0.985 0.99 0.98
##
## $CCF$CRUK0005
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 2 5 TRUE TRUE 1 1 0.97 1
## 2 1 1 TRUE FALSE 0 0 0.8 0
##
## $CCF$CRUK0006
## # A tibble: 3 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1
## 2 2 1 TRUE FALSE 0 0.93
## 3 7 1 TRUE FALSE 0.99 0.06
##
## $CCF$CRUK0007
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.98 0.93
##
## $CCF$CRUK0008
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 2 5 TRUE TRUE 0.99 1
## 2 3 1 TRUE FALSE 0.86 0
##
## $CCF$CRUK0009
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 0.99 0.99 0.98 0.99
## 2 2 1 TRUE FALSE 0 0.93 0 0.96
##
## $CCF$CRUK0010
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.95 0.98
##
## $CCF$CRUK0011
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.97 1
## 2 3 1 TRUE FALSE 0.95 0 0
##
## $CCF$CRUK0012
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.98 0.95
##
## $CCF$CRUK0013
## # A tibble: 4 x 9
## cluster nMuts is.driver is.clonal LN1 LN2 R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.99 0.99 0.99 0.99
## 2 2 1 TRUE FALSE 0 0 0 0.75 0
## 3 3 1 TRUE FALSE 0.97 0.96 0.01 0.580 0.94
## 4 4 1 TRUE FALSE 0 0 0.97 0.37 0.01
##
## $CCF$CRUK0014
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.96 0.96
## 2 2 1 TRUE FALSE 0.35 0.01
##
## $CCF$CRUK0015
## # A tibble: 3 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.99 0.99
## 2 2 1 TRUE FALSE 0.94 0.01
## 3 3 1 TRUE FALSE 0.01 0.65
##
## $CCF$CRUK0016
## # A tibble: 5 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 0.99 0.99
## 2 16 2 TRUE FALSE 0.97 0
## 3 10 1 TRUE FALSE 0.34 0.3
## 4 2 1 TRUE FALSE 0.53 0
## 5 6 1 TRUE FALSE 0.31 0.53
##
## $CCF$CRUK0017
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 1 1 1 1
## 2 3 1 TRUE FALSE 0 0.94 0.95 0.59
##
## $CCF$CRUK0018
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1
##
## $CCF$CRUK0019
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.97 0.96
##
## $CCF$CRUK0020
## # A tibble: 4 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 7 TRUE TRUE 1 1
## 2 2 1 TRUE FALSE 0.87 0
## 3 3 1 TRUE FALSE 0.9 0.08
## 4 4 1 TRUE FALSE 0 0.85
##
## $CCF$CRUK0021
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 0.99
##
## $CCF$CRUK0022
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.99 0.99
## 2 2 1 TRUE FALSE 0.85 0
##
## $CCF$CRUK0023
## # A tibble: 3 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.99 0.98 0.99 0.95
## 2 4 2 TRUE FALSE 0.01 0.945 0 0
## 3 2 1 TRUE FALSE 0.81 0 0 0
##
## $CCF$CRUK0024
## # A tibble: 3 x 8
## cluster nMuts is.driver is.clonal R1 R3 R4 R6
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1
## 2 3 1 TRUE FALSE 0.88 0.97 0.95 0
## 3 4 1 TRUE FALSE 0.83 0 0 0
##
## $CCF$CRUK0025
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 1 1 1
##
## $CCF$CRUK0026
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 0.98 0.98
##
## $CCF$CRUK0027
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.96 1
## 2 2 1 TRUE FALSE 0 0.99
##
## $CCF$CRUK0028
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.975 0.95
##
## $CCF$CRUK0029
## # A tibble: 1 x 10
## cluster nMuts is.driver is.clonal R2 R4 R5 R6 R7 R8
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 0.99 0.98 1 1 1
##
## $CCF$CRUK0030
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 1 0.98 0.98
##
## $CCF$CRUK0031
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1
## 2 6 1 TRUE FALSE 0.88 0.05 0
##
## $CCF$CRUK0032
## # A tibble: 3 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1
## 2 4 1 TRUE FALSE 0 0.97 0 0.98
## 3 6 1 TRUE FALSE 0 0 0 0.3
##
## $CCF$CRUK0033
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.99 0.98
##
## $CCF$CRUK0034
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 1 1 1
## 2 4 1 TRUE FALSE 0 0.5 0
##
## $CCF$CRUK0035
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal LN1 R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.98 0.98 0.99 0.99
## 2 4 1 TRUE FALSE 0 0.8 0 0.01
##
## $CCF$CRUK0036
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 0.99 0.98 0.97 1
##
## $CCF$CRUK0037
## # A tibble: 1 x 9
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.99 1 1 1 1
##
## $CCF$CRUK0038
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.99
## 2 3 1 TRUE FALSE 0 0.38
##
## $CCF$CRUK0039
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 0.98
##
## $CCF$CRUK0040
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 0.99 0.99
##
## $CCF$CRUK0041
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.98 0.99 0.99 0.99
##
## $CCF$CRUK0042
## # A tibble: 1 x 5
## cluster nMuts is.driver is.clonal R1
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 1 TRUE TRUE 0.91
##
## $CCF$CRUK0043
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.98
##
## $CCF$CRUK0044
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 1 1
##
## $CCF$CRUK0045
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.98 0.98
##
## $CCF$CRUK0046
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 1 0.98 0.995 0.96
##
## $CCF$CRUK0047
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 0.99 1
##
## $CCF$CRUK0048
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 7 TRUE TRUE 1 1 1
##
## $CCF$CRUK0049
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 1 1
##
## $CCF$CRUK0050
## # A tibble: 1 x 9
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.99 0.99 0.99 1 0.99
##
## $CCF$CRUK0051
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1
## 2 3 1 TRUE FALSE 0.97 0 0
##
## $CCF$CRUK0052
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R1 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 8 TRUE TRUE 1 1 1
## 2 2 1 TRUE FALSE 0 0 0.86
##
## $CCF$CRUK0054
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.99
##
## $CCF$CRUK0055
## # A tibble: 2 x 5
## cluster nMuts is.driver is.clonal R2
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 2 TRUE TRUE 1
## 2 2 1 TRUE FALSE 0.32
##
## $CCF$CRUK0056
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 1 1 1
## 2 3 1 TRUE FALSE 0 0.12 0.98
##
## $CCF$CRUK0057
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 1 1
##
## $CCF$CRUK0058
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.98 0.99
##
## $CCF$CRUK0059
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.98
##
## $CCF$CRUK0060
## # A tibble: 1 x 5
## cluster nMuts is.driver is.clonal R1
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 11 TRUE TRUE 1
##
## $CCF$CRUK0061
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 1
##
## $CCF$CRUK0062
## # A tibble: 4 x 11
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5 R6
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 4 4 TRUE TRUE 0.99 0.99 0.98 0.97 0.99 0.99
## 2 1 1 TRUE FALSE 0 0.01 0 0 0 0.94
## 3 16 1 TRUE FALSE 0.93 0.86 0.08 0.02 0.12 0
## 4 2 1 TRUE FALSE 0.84 0.83 0.02 0 0 0
## # … with 1 more variable: R7 <dbl>
##
## $CCF$CRUK0063
## # A tibble: 4 x 9
## cluster nMuts is.driver is.clonal R3 R4 R5 R6 R7
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2 7 TRUE TRUE 0.93 0.99 0.99 0.99 1
## 2 1 2 TRUE FALSE 0 0.99 0.99 0.98 1
## 3 10 1 TRUE FALSE 0 0.99 0.99 0.98 1
## 4 6 1 TRUE FALSE 0 0.02 0.7 0.36 0.55
##
## $CCF$CRUK0064
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 2 2 TRUE FALSE 0.64 0.11
## 2 1 1 TRUE TRUE 1 1
##
## $CCF$CRUK0065
## # A tibble: 3 x 10
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5 R6
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 0.99 0.99 1 1 1
## 2 2 3 TRUE FALSE 0 0 0 0 0.48 0
## 3 6 2 TRUE FALSE 0 0 0 0 0.01 0.83
##
## $CCF$CRUK0066
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 7 TRUE TRUE 0.99 1 1 0.99
## 2 9 1 TRUE FALSE 0 0.91 0.01 0
##
## $CCF$CRUK0067
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 0.99 1
## 2 2 1 TRUE FALSE 0.61 0.83
##
## $CCF$CRUK0068
## # A tibble: 4 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 0.99 1 1 1
## 2 3 1 TRUE FALSE 0.5 0 0 0
## 3 4 1 TRUE FALSE 0.98 0.37 0.99 0.01
## 4 9 1 TRUE FALSE 0 0 0 0.69
##
## $CCF$CRUK0069
## # A tibble: 2 x 9
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1 1
## 2 13 1 TRUE FALSE 0.93 0.42 0.32 0.94 0.96
##
## $CCF$CRUK0070
## # A tibble: 3 x 9
## cluster nMuts is.driver is.clonal R1 R2 R4 R6 R7
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1 1
## 2 2 1 TRUE FALSE 0 0 0 0.95 0.98
## 3 3 1 TRUE FALSE 0.95 0.96 0.98 0 0.01
##
## $CCF$CRUK0071
## # A tibble: 2 x 10
## cluster nMuts is.driver is.clonal R1 R2 R3 R5 R6 R7
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 1 0.99 1 1 1 1
## 2 4 1 TRUE FALSE 0 0.570 0 0 0 0
##
## $CCF$CRUK0072
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 1 0.99 0.99
##
## $CCF$CRUK0073
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 8 TRUE TRUE 1 1
## 2 2 1 TRUE FALSE 0 0.93
##
## $CCF$CRUK0074
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 0.99 1
## 2 3 1 TRUE FALSE 0 0.99
##
## $CCF$CRUK0075
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 7 TRUE TRUE 1 0.99
## 2 2 1 TRUE FALSE 0.15 0.98
##
## $CCF$CRUK0076
## # A tibble: 3 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 1 1 1 1
## 2 2 1 TRUE FALSE 0.93 0 0.28 0
## 3 3 1 TRUE FALSE 0.93 0 0.81 0
##
## $CCF$CRUK0077
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 1 1 1 1
##
## $CCF$CRUK0078
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 1 1 1
##
## $CCF$CRUK0079
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 1 0.99 1 1
##
## $CCF$CRUK0080
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal R3 R4 R5 R6
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1
## 2 3 1 TRUE FALSE 0 0 0.97 0.83
##
## $CCF$CRUK0081
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R5
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 1 0.99
## 2 3 1 TRUE FALSE 0.93 0.01
##
## $CCF$CRUK0082
## # A tibble: 1 x 9
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 8 TRUE TRUE 1 1 1 1 1
##
## $CCF$CRUK0083
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 7 TRUE TRUE 1 1 1 0.99
##
## $CCF$CRUK0084
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 1 1 1 1
##
## $CCF$CRUK0085
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1
##
## $CCF$CRUK0086
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 1 1 1
##
## $CCF$CRUK0087
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1
##
## $CCF$CRUK0088
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 1 1
##
## $CCF$CRUK0089
## # A tibble: 1 x 5
## cluster nMuts is.driver is.clonal R2
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 3 TRUE TRUE 0.99
##
## $CCF$CRUK0090
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 1 1
##
## $CCF$CRUK0091
## # A tibble: 1 x 5
## cluster nMuts is.driver is.clonal R2
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 3 TRUE TRUE 1
##
## $CCF$CRUK0092
## # A tibble: 1 x 5
## cluster nMuts is.driver is.clonal R1
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 5 TRUE TRUE 1
##
## $CCF$CRUK0093
## # A tibble: 1 x 5
## cluster nMuts is.driver is.clonal R1
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 7 TRUE TRUE 0.96
##
## $CCF$CRUK0094
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.98 0.98 0.97 0.99
##
## $CCF$CRUK0095
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.99 0.99 0.98
##
## $CCF$CRUK0096
## # A tibble: 1 x 11
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5 R6
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 1 1 1 1 1 1
## # … with 1 more variable: R7 <dbl>
##
## $CCF$CRUK0097
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.995 0.98
##
## $CCF$CRUK0098
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 1 1 1
## 2 3 1 TRUE FALSE 0.96 0.91 0
##
## $CCF$CRUK0099
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R3 R6 R7
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.95 0.97 0.91 1
##
## $CCF$CRUK0100
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 1 1 1
##
##
## $n
## $n$patients
## [1] 99
##
## $n$variants
## [1] 450
##
## $n$drivers
## [1] 79
##
##
## $CCF_parser
## <srcref: file "/Users/gcaravagna/Documents/Github/revolver/R/CCF_parser.R" chars 25:14 to 36:1>
## <bytecode: 0x7f868f5a9d78>
## <environment: namespace:revolver>
##
## $phylogenies
## $phylogenies$CRUK0001
## $phylogenies$CRUK0001$`1`
## [ ctree - ctree rank 1/3 for CRUK0001 ]
##
## # A tibble: 4 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 3 4 TRUE TRUE 0.99 0.99 1
## 2 1 1 TRUE FALSE 0.86 0 0
## 3 2 1 TRUE FALSE 0.19 0 0.95
## 4 5 1 TRUE FALSE 0.82 0 0.71
##
## Tree shape (drivers annotated)
##
## \-GL
## \-3 [R2] :: TP53, MGA, WRN, EGFR
## |-1 :: NF1
## | \-5 :: PASK
## \-2 :: ARHGAP35
##
## Information transfer
##
## GL ---> TP53
## GL ---> MGA
## GL ---> WRN
## GL ---> EGFR
## TP53 ---> NF1
## MGA ---> NF1
## WRN ---> NF1
## EGFR ---> NF1
## TP53 ---> ARHGAP35
## MGA ---> ARHGAP35
## WRN ---> ARHGAP35
## EGFR ---> ARHGAP35
## NF1 ---> PASK
##
## Tree score 0.111111111111111
##
## $phylogenies$CRUK0001$`2`
## [ ctree - ctree rank 2/3 for CRUK0001 ]
##
## # A tibble: 4 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 3 4 TRUE TRUE 0.99 0.99 1
## 2 1 1 TRUE FALSE 0.86 0 0
## 3 2 1 TRUE FALSE 0.19 0 0.95
## 4 5 1 TRUE FALSE 0.82 0 0.71
##
## Tree shape (drivers annotated)
##
## \-GL
## \-3 [R2] :: TP53, MGA, WRN, EGFR
## |-2 :: ARHGAP35
## | \-5 :: PASK
## \-1 :: NF1
##
## Information transfer
##
## GL ---> TP53
## GL ---> MGA
## GL ---> WRN
## GL ---> EGFR
## TP53 ---> NF1
## MGA ---> NF1
## WRN ---> NF1
## EGFR ---> NF1
## TP53 ---> ARHGAP35
## MGA ---> ARHGAP35
## WRN ---> ARHGAP35
## EGFR ---> ARHGAP35
## ARHGAP35 ---> PASK
##
## Tree score 0.111111111111111
##
## $phylogenies$CRUK0001$`3`
## [ ctree - ctree rank 3/3 for CRUK0001 ]
##
## # A tibble: 4 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 3 4 TRUE TRUE 0.99 0.99 1
## 2 1 1 TRUE FALSE 0.86 0 0
## 3 2 1 TRUE FALSE 0.19 0 0.95
## 4 5 1 TRUE FALSE 0.82 0 0.71
##
## Tree shape (drivers annotated)
##
## \-GL
## \-3 [R2] :: TP53, MGA, WRN, EGFR
## \-1 :: NF1
## \-5 :: PASK
## \-2 :: ARHGAP35
##
## Information transfer
##
## GL ---> TP53
## GL ---> MGA
## GL ---> WRN
## GL ---> EGFR
## TP53 ---> NF1
## MGA ---> NF1
## WRN ---> NF1
## EGFR ---> NF1
## PASK ---> ARHGAP35
## NF1 ---> PASK
##
## Tree score 0.111111111111111
##
##
## $phylogenies$CRUK0002
## $phylogenies$CRUK0002$`1`
## [ ctree - ctree rank 1/2 for CRUK0002 ]
##
## # A tibble: 4 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE FALSE 0 0.92 0
## 2 2 2 TRUE TRUE 0.99 0.98 0.99
## 3 5 1 TRUE FALSE 0.78 0 0
## 4 6 1 TRUE FALSE 0.96 0.03 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-2 :: MET, TERT
## |-6 :: EP300
## | \-5 :: NF1
## \-1 :: RB1, IKZF1, KRAS
##
## Information transfer
##
## MET ---> RB1
## MET ---> IKZF1
## MET ---> KRAS
## TERT ---> RB1
## TERT ---> IKZF1
## TERT ---> KRAS
## GL ---> MET
## GL ---> TERT
## EP300 ---> NF1
## MET ---> EP300
## TERT ---> EP300
##
## Tree score 0.75
##
## $phylogenies$CRUK0002$`2`
## [ ctree - ctree rank 2/2 for CRUK0002 ]
##
## # A tibble: 4 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE FALSE 0 0.92 0
## 2 2 2 TRUE TRUE 0.99 0.98 0.99
## 3 5 1 TRUE FALSE 0.78 0 0
## 4 6 1 TRUE FALSE 0.96 0.03 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-2 :: MET, TERT
## \-1 :: RB1, IKZF1, KRAS
## \-6 :: EP300
## \-5 :: NF1
##
## Information transfer
##
## MET ---> RB1
## MET ---> IKZF1
## MET ---> KRAS
## TERT ---> RB1
## TERT ---> IKZF1
## TERT ---> KRAS
## GL ---> MET
## GL ---> TERT
## EP300 ---> NF1
## RB1 ---> EP300
## IKZF1 ---> EP300
## KRAS ---> EP300
##
## Tree score 0.0833333333333333
##
##
## $phylogenies$CRUK0003
## $phylogenies$CRUK0003$`1`
## [ ctree - ctree rank 1/1 for CRUK0003 ]
##
## # A tibble: 2 x 9
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R6
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.98 0.97 0.87 0.97 0.99
## 2 4 1 TRUE FALSE 0 0 0.49 0 0.01
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R4] :: PIK3CA, EGFR, CDKN2A
## \-4 :: CTNNB1
##
## Information transfer
##
## GL ---> PIK3CA
## GL ---> EGFR
## GL ---> CDKN2A
## PIK3CA ---> CTNNB1
## EGFR ---> CTNNB1
## CDKN2A ---> CTNNB1
##
## Tree score 1
##
##
## $phylogenies$CRUK0004
## $phylogenies$CRUK0004$`1`
## [ ctree - ctree rank 1/1 for CRUK0004 ]
##
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 2 TRUE FALSE 0 0 0.95 0.01
## 2 2 2 TRUE TRUE 0.99 0.985 0.99 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-2 [R1, R2] :: TP53, EGFR
## \-1 :: SMAD4, NOTCH1
##
## Information transfer
##
## TP53 ---> SMAD4
## TP53 ---> NOTCH1
## EGFR ---> SMAD4
## EGFR ---> NOTCH1
## GL ---> TP53
## GL ---> EGFR
##
## Tree score 1
##
##
## $phylogenies$CRUK0005
## $phylogenies$CRUK0005$`1`
## [ ctree - ctree rank 1/1 for CRUK0005 ]
##
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 2 5 TRUE TRUE 1 1 0.97 1
## 2 1 1 TRUE FALSE 0 0 0.8 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-2 [R1, R2, R4] :: CMTR2, TP53, BRAF, PASK, TERT
## \-1 :: NRAS
##
## Information transfer
##
## GL ---> CMTR2
## GL ---> TP53
## GL ---> BRAF
## GL ---> PASK
## GL ---> TERT
## CMTR2 ---> NRAS
## TP53 ---> NRAS
## BRAF ---> NRAS
## PASK ---> NRAS
## TERT ---> NRAS
##
## Tree score 1
##
##
## $phylogenies$CRUK0006
## $phylogenies$CRUK0006$`1`
## [ ctree - ctree rank 1/2 for CRUK0006 ]
##
## # A tibble: 3 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1
## 2 2 1 TRUE FALSE 0 0.93
## 3 7 1 TRUE FALSE 0.99 0.06
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: PLXNB2, TP53, KEAP1, TERT
## |-7 :: FANCC
## \-2 :: MAP3K1
##
## Information transfer
##
## GL ---> PLXNB2
## GL ---> TP53
## GL ---> KEAP1
## GL ---> TERT
## PLXNB2 ---> MAP3K1
## TP53 ---> MAP3K1
## KEAP1 ---> MAP3K1
## TERT ---> MAP3K1
## PLXNB2 ---> FANCC
## TP53 ---> FANCC
## KEAP1 ---> FANCC
## TERT ---> FANCC
##
## Tree score 0.666666666666667
##
## $phylogenies$CRUK0006$`2`
## [ ctree - ctree rank 2/2 for CRUK0006 ]
##
## # A tibble: 3 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1
## 2 2 1 TRUE FALSE 0 0.93
## 3 7 1 TRUE FALSE 0.99 0.06
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: PLXNB2, TP53, KEAP1, TERT
## \-2 :: MAP3K1
## \-7 :: FANCC
##
## Information transfer
##
## GL ---> PLXNB2
## GL ---> TP53
## GL ---> KEAP1
## GL ---> TERT
## PLXNB2 ---> MAP3K1
## TP53 ---> MAP3K1
## KEAP1 ---> MAP3K1
## TERT ---> MAP3K1
## MAP3K1 ---> FANCC
##
## Tree score 0.166666666666667
##
##
## $phylogenies$CRUK0007
## $phylogenies$CRUK0007$`1`
## [ ctree - ctree rank 1/1 for CRUK0007 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.98 0.93
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: PIK3CA, EGFR, SGK223
##
## Information transfer
##
## GL ---> PIK3CA
## GL ---> EGFR
## GL ---> SGK223
##
## Tree score 1
##
##
## $phylogenies$CRUK0008
## $phylogenies$CRUK0008$`1`
## [ ctree - ctree rank 1/1 for CRUK0008 ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 2 5 TRUE TRUE 0.99 1
## 2 3 1 TRUE FALSE 0.86 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-2 [R2] :: KEAP1, STK11, PRDM1, U2AF1, MYC
## \-3 :: ARID2
##
## Information transfer
##
## GL ---> KEAP1
## GL ---> STK11
## GL ---> PRDM1
## GL ---> U2AF1
## GL ---> MYC
## KEAP1 ---> ARID2
## STK11 ---> ARID2
## PRDM1 ---> ARID2
## U2AF1 ---> ARID2
## MYC ---> ARID2
##
## Tree score 1
##
##
## $phylogenies$CRUK0009
## $phylogenies$CRUK0009$`1`
## [ ctree - ctree rank 1/1 for CRUK0009 ]
##
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 0.99 0.99 0.98 0.99
## 2 2 1 TRUE FALSE 0 0.93 0 0.96
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R3] :: BRAF, TP53, ARHGAP35, KMT2C, NFE2L2, MET
## \-2 :: TERT
##
## Information transfer
##
## GL ---> BRAF
## GL ---> TP53
## GL ---> ARHGAP35
## GL ---> KMT2C
## GL ---> NFE2L2
## GL ---> MET
## BRAF ---> TERT
## TP53 ---> TERT
## ARHGAP35 ---> TERT
## KMT2C ---> TERT
## NFE2L2 ---> TERT
## MET ---> TERT
##
## Tree score 1
##
##
## $phylogenies$CRUK0010
## $phylogenies$CRUK0010$`1`
## [ ctree - ctree rank 1/1 for CRUK0010 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.95 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: SETD2, EGFR, TERT
##
## Information transfer
##
## GL ---> SETD2
## GL ---> EGFR
## GL ---> TERT
##
## Tree score 1
##
##
## $phylogenies$CRUK0011
## $phylogenies$CRUK0011$`1`
## [ ctree - ctree rank 1/1 for CRUK0011 ]
##
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.97 1
## 2 3 1 TRUE FALSE 0.95 0 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R2, R3] :: KRAS
## \-3 :: FLT4
##
## Information transfer
##
## GL ---> KRAS
## KRAS ---> FLT4
##
## Tree score 1
##
##
## $phylogenies$CRUK0012
## $phylogenies$CRUK0012$`1`
## [ ctree - ctree rank 1/1 for CRUK0012 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.98 0.95
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: EGFR
##
## Information transfer
##
## GL ---> EGFR
##
## Tree score 1
##
##
## $phylogenies$CRUK0013
## $phylogenies$CRUK0013$`1`
## [ ctree - ctree rank 1/4 for CRUK0013 ]
##
## # A tibble: 4 x 9
## cluster nMuts is.driver is.clonal LN1 LN2 R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.99 0.99 0.99 0.99
## 2 2 1 TRUE FALSE 0 0 0 0.75 0
## 3 3 1 TRUE FALSE 0.97 0.96 0.01 0.580 0.94
## 4 4 1 TRUE FALSE 0 0 0.97 0.37 0.01
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: STK11
## |-3 :: KRAS
## |-4 :: EGFR
## \-2 :: NOTCH1
##
## Information transfer
##
## GL ---> STK11
## STK11 ---> NOTCH1
## STK11 ---> KRAS
## STK11 ---> EGFR
##
## Tree score 0.3
##
## $phylogenies$CRUK0013$`2`
## [ ctree - ctree rank 2/4 for CRUK0013 ]
##
## # A tibble: 4 x 9
## cluster nMuts is.driver is.clonal LN1 LN2 R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.99 0.99 0.99 0.99
## 2 2 1 TRUE FALSE 0 0 0 0.75 0
## 3 3 1 TRUE FALSE 0.97 0.96 0.01 0.580 0.94
## 4 4 1 TRUE FALSE 0 0 0.97 0.37 0.01
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: STK11
## |-3 :: KRAS
## | \-4 :: EGFR
## \-2 :: NOTCH1
##
## Information transfer
##
## GL ---> STK11
## STK11 ---> NOTCH1
## STK11 ---> KRAS
## KRAS ---> EGFR
##
## Tree score 0.24
##
## $phylogenies$CRUK0013$`3`
## [ ctree - ctree rank 3/4 for CRUK0013 ]
##
## # A tibble: 4 x 9
## cluster nMuts is.driver is.clonal LN1 LN2 R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.99 0.99 0.99 0.99
## 2 2 1 TRUE FALSE 0 0 0 0.75 0
## 3 3 1 TRUE FALSE 0.97 0.96 0.01 0.580 0.94
## 4 4 1 TRUE FALSE 0 0 0.97 0.37 0.01
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: STK11
## |-2 :: NOTCH1
## | \-3 :: KRAS
## \-4 :: EGFR
##
## Information transfer
##
## GL ---> STK11
## STK11 ---> NOTCH1
## NOTCH1 ---> KRAS
## STK11 ---> EGFR
##
## Tree score 0.02
##
## $phylogenies$CRUK0013$`4`
## [ ctree - ctree rank 4/4 for CRUK0013 ]
##
## # A tibble: 4 x 9
## cluster nMuts is.driver is.clonal LN1 LN2 R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.99 0.99 0.99 0.99
## 2 2 1 TRUE FALSE 0 0 0 0.75 0
## 3 3 1 TRUE FALSE 0.97 0.96 0.01 0.580 0.94
## 4 4 1 TRUE FALSE 0 0 0.97 0.37 0.01
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: STK11
## \-2 :: NOTCH1
## \-3 :: KRAS
## \-4 :: EGFR
##
## Information transfer
##
## GL ---> STK11
## STK11 ---> NOTCH1
## NOTCH1 ---> KRAS
## KRAS ---> EGFR
##
## Tree score 0.02
##
##
## $phylogenies$CRUK0014
## $phylogenies$CRUK0014$`1`
## [ ctree - ctree rank 1/1 for CRUK0014 ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.96 0.96
## 2 2 1 TRUE FALSE 0.35 0.01
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53, KRAS
## \-2 :: RNF43
##
## Information transfer
##
## GL ---> TP53
## GL ---> KRAS
## TP53 ---> RNF43
## KRAS ---> RNF43
##
## Tree score 1
##
##
## $phylogenies$CRUK0015
## $phylogenies$CRUK0015$`1`
## [ ctree - ctree rank 1/1 for CRUK0015 ]
##
## # A tibble: 3 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.99 0.99
## 2 2 1 TRUE FALSE 0.94 0.01
## 3 3 1 TRUE FALSE 0.01 0.65
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: BAP1, EGFR
## |-2 :: TP53
## \-3 :: RB1
##
## Information transfer
##
## GL ---> BAP1
## GL ---> EGFR
## BAP1 ---> TP53
## EGFR ---> TP53
## BAP1 ---> RB1
## EGFR ---> RB1
##
## Tree score 1
##
##
## $phylogenies$CRUK0016
## $phylogenies$CRUK0016$`1`
## [ ctree - ctree rank 1/13 for CRUK0016 ]
##
## # A tibble: 5 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 0.99 0.99
## 2 16 2 TRUE FALSE 0.97 0
## 3 10 1 TRUE FALSE 0.34 0.3
## 4 2 1 TRUE FALSE 0.53 0
## 5 6 1 TRUE FALSE 0.31 0.53
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53, FAT1, SPEN, CBLB, TERT, CDKN2A
## |-16 :: LATS1, ARID1B
## | \-2 :: ASXL1
## |-10 :: DNM2
## \-6 :: PTPRC
##
## Information transfer
##
## GL ---> TP53
## GL ---> FAT1
## GL ---> SPEN
## GL ---> CBLB
## GL ---> TERT
## GL ---> CDKN2A
## TP53 ---> LATS1
## TP53 ---> ARID1B
## FAT1 ---> LATS1
## FAT1 ---> ARID1B
## SPEN ---> LATS1
## SPEN ---> ARID1B
## CBLB ---> LATS1
## CBLB ---> ARID1B
## TERT ---> LATS1
## TERT ---> ARID1B
## CDKN2A ---> LATS1
## CDKN2A ---> ARID1B
## TP53 ---> DNM2
## FAT1 ---> DNM2
## SPEN ---> DNM2
## CBLB ---> DNM2
## TERT ---> DNM2
## CDKN2A ---> DNM2
## LATS1 ---> ASXL1
## ARID1B ---> ASXL1
## TP53 ---> PTPRC
## FAT1 ---> PTPRC
## SPEN ---> PTPRC
## CBLB ---> PTPRC
## TERT ---> PTPRC
## CDKN2A ---> PTPRC
##
## Tree score 0.03125
##
## $phylogenies$CRUK0016$`2`
## [ ctree - ctree rank 2/13 for CRUK0016 ]
##
## # A tibble: 5 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 0.99 0.99
## 2 16 2 TRUE FALSE 0.97 0
## 3 10 1 TRUE FALSE 0.34 0.3
## 4 2 1 TRUE FALSE 0.53 0
## 5 6 1 TRUE FALSE 0.31 0.53
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53, FAT1, SPEN, CBLB, TERT, CDKN2A
## \-16 :: LATS1, ARID1B
## |-2 :: ASXL1
## | \-10 :: DNM2
## \-6 :: PTPRC
##
## Information transfer
##
## GL ---> TP53
## GL ---> FAT1
## GL ---> SPEN
## GL ---> CBLB
## GL ---> TERT
## GL ---> CDKN2A
## TP53 ---> LATS1
## TP53 ---> ARID1B
## FAT1 ---> LATS1
## FAT1 ---> ARID1B
## SPEN ---> LATS1
## SPEN ---> ARID1B
## CBLB ---> LATS1
## CBLB ---> ARID1B
## TERT ---> LATS1
## TERT ---> ARID1B
## CDKN2A ---> LATS1
## CDKN2A ---> ARID1B
## ASXL1 ---> DNM2
## LATS1 ---> ASXL1
## ARID1B ---> ASXL1
## LATS1 ---> PTPRC
## ARID1B ---> PTPRC
##
## Tree score 0.015625
##
## $phylogenies$CRUK0016$`3`
## [ ctree - ctree rank 3/13 for CRUK0016 ]
##
## # A tibble: 5 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 0.99 0.99
## 2 16 2 TRUE FALSE 0.97 0
## 3 10 1 TRUE FALSE 0.34 0.3
## 4 2 1 TRUE FALSE 0.53 0
## 5 6 1 TRUE FALSE 0.31 0.53
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53, FAT1, SPEN, CBLB, TERT, CDKN2A
## \-16 :: LATS1, ARID1B
## \-2 :: ASXL1
## \-6 :: PTPRC
## \-10 :: DNM2
##
## Information transfer
##
## GL ---> TP53
## GL ---> FAT1
## GL ---> SPEN
## GL ---> CBLB
## GL ---> TERT
## GL ---> CDKN2A
## TP53 ---> LATS1
## TP53 ---> ARID1B
## FAT1 ---> LATS1
## FAT1 ---> ARID1B
## SPEN ---> LATS1
## SPEN ---> ARID1B
## CBLB ---> LATS1
## CBLB ---> ARID1B
## TERT ---> LATS1
## TERT ---> ARID1B
## CDKN2A ---> LATS1
## CDKN2A ---> ARID1B
## PTPRC ---> DNM2
## LATS1 ---> ASXL1
## ARID1B ---> ASXL1
## ASXL1 ---> PTPRC
##
## Tree score 0.015625
##
## $phylogenies$CRUK0016$`4`
## [ ctree - ctree rank 4/13 for CRUK0016 ]
##
## # A tibble: 5 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 0.99 0.99
## 2 16 2 TRUE FALSE 0.97 0
## 3 10 1 TRUE FALSE 0.34 0.3
## 4 2 1 TRUE FALSE 0.53 0
## 5 6 1 TRUE FALSE 0.31 0.53
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53, FAT1, SPEN, CBLB, TERT, CDKN2A
## \-16 :: LATS1, ARID1B
## |-10 :: DNM2
## | \-6 :: PTPRC
## \-2 :: ASXL1
##
## Information transfer
##
## GL ---> TP53
## GL ---> FAT1
## GL ---> SPEN
## GL ---> CBLB
## GL ---> TERT
## GL ---> CDKN2A
## TP53 ---> LATS1
## TP53 ---> ARID1B
## FAT1 ---> LATS1
## FAT1 ---> ARID1B
## SPEN ---> LATS1
## SPEN ---> ARID1B
## CBLB ---> LATS1
## CBLB ---> ARID1B
## TERT ---> LATS1
## TERT ---> ARID1B
## CDKN2A ---> LATS1
## CDKN2A ---> ARID1B
## LATS1 ---> DNM2
## ARID1B ---> DNM2
## LATS1 ---> ASXL1
## ARID1B ---> ASXL1
## DNM2 ---> PTPRC
##
## Tree score 0.015625
##
## $phylogenies$CRUK0016$`5`
## [ ctree - ctree rank 5/13 for CRUK0016 ]
##
## # A tibble: 5 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 0.99 0.99
## 2 16 2 TRUE FALSE 0.97 0
## 3 10 1 TRUE FALSE 0.34 0.3
## 4 2 1 TRUE FALSE 0.53 0
## 5 6 1 TRUE FALSE 0.31 0.53
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53, FAT1, SPEN, CBLB, TERT, CDKN2A
## \-16 :: LATS1, ARID1B
## \-2 :: ASXL1
## \-10 :: DNM2
## \-6 :: PTPRC
##
## Information transfer
##
## GL ---> TP53
## GL ---> FAT1
## GL ---> SPEN
## GL ---> CBLB
## GL ---> TERT
## GL ---> CDKN2A
## TP53 ---> LATS1
## TP53 ---> ARID1B
## FAT1 ---> LATS1
## FAT1 ---> ARID1B
## SPEN ---> LATS1
## SPEN ---> ARID1B
## CBLB ---> LATS1
## CBLB ---> ARID1B
## TERT ---> LATS1
## TERT ---> ARID1B
## CDKN2A ---> LATS1
## CDKN2A ---> ARID1B
## ASXL1 ---> DNM2
## LATS1 ---> ASXL1
## ARID1B ---> ASXL1
## DNM2 ---> PTPRC
##
## Tree score 0.015625
##
## $phylogenies$CRUK0016$`6`
## [ ctree - ctree rank 6/13 for CRUK0016 ]
##
## # A tibble: 5 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 0.99 0.99
## 2 16 2 TRUE FALSE 0.97 0
## 3 10 1 TRUE FALSE 0.34 0.3
## 4 2 1 TRUE FALSE 0.53 0
## 5 6 1 TRUE FALSE 0.31 0.53
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53, FAT1, SPEN, CBLB, TERT, CDKN2A
## |-16 :: LATS1, ARID1B
## | \-2 :: ASXL1
## | \-10 :: DNM2
## \-6 :: PTPRC
##
## Information transfer
##
## GL ---> TP53
## GL ---> FAT1
## GL ---> SPEN
## GL ---> CBLB
## GL ---> TERT
## GL ---> CDKN2A
## TP53 ---> LATS1
## TP53 ---> ARID1B
## FAT1 ---> LATS1
## FAT1 ---> ARID1B
## SPEN ---> LATS1
## SPEN ---> ARID1B
## CBLB ---> LATS1
## CBLB ---> ARID1B
## TERT ---> LATS1
## TERT ---> ARID1B
## CDKN2A ---> LATS1
## CDKN2A ---> ARID1B
## ASXL1 ---> DNM2
## LATS1 ---> ASXL1
## ARID1B ---> ASXL1
## TP53 ---> PTPRC
## FAT1 ---> PTPRC
## SPEN ---> PTPRC
## CBLB ---> PTPRC
## TERT ---> PTPRC
## CDKN2A ---> PTPRC
##
## Tree score 0.015625
##
## $phylogenies$CRUK0016$`7`
## [ ctree - ctree rank 7/13 for CRUK0016 ]
##
## # A tibble: 5 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 0.99 0.99
## 2 16 2 TRUE FALSE 0.97 0
## 3 10 1 TRUE FALSE 0.34 0.3
## 4 2 1 TRUE FALSE 0.53 0
## 5 6 1 TRUE FALSE 0.31 0.53
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53, FAT1, SPEN, CBLB, TERT, CDKN2A
## |-16 :: LATS1, ARID1B
## | |-6 :: PTPRC
## | \-2 :: ASXL1
## \-10 :: DNM2
##
## Information transfer
##
## GL ---> TP53
## GL ---> FAT1
## GL ---> SPEN
## GL ---> CBLB
## GL ---> TERT
## GL ---> CDKN2A
## TP53 ---> LATS1
## TP53 ---> ARID1B
## FAT1 ---> LATS1
## FAT1 ---> ARID1B
## SPEN ---> LATS1
## SPEN ---> ARID1B
## CBLB ---> LATS1
## CBLB ---> ARID1B
## TERT ---> LATS1
## TERT ---> ARID1B
## CDKN2A ---> LATS1
## CDKN2A ---> ARID1B
## TP53 ---> DNM2
## FAT1 ---> DNM2
## SPEN ---> DNM2
## CBLB ---> DNM2
## TERT ---> DNM2
## CDKN2A ---> DNM2
## LATS1 ---> ASXL1
## ARID1B ---> ASXL1
## LATS1 ---> PTPRC
## ARID1B ---> PTPRC
##
## Tree score 0.015625
##
## $phylogenies$CRUK0016$`8`
## [ ctree - ctree rank 8/13 for CRUK0016 ]
##
## # A tibble: 5 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 0.99 0.99
## 2 16 2 TRUE FALSE 0.97 0
## 3 10 1 TRUE FALSE 0.34 0.3
## 4 2 1 TRUE FALSE 0.53 0
## 5 6 1 TRUE FALSE 0.31 0.53
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53, FAT1, SPEN, CBLB, TERT, CDKN2A
## |-10 :: DNM2
## | \-6 :: PTPRC
## \-16 :: LATS1, ARID1B
## \-2 :: ASXL1
##
## Information transfer
##
## GL ---> TP53
## GL ---> FAT1
## GL ---> SPEN
## GL ---> CBLB
## GL ---> TERT
## GL ---> CDKN2A
## TP53 ---> LATS1
## TP53 ---> ARID1B
## FAT1 ---> LATS1
## FAT1 ---> ARID1B
## SPEN ---> LATS1
## SPEN ---> ARID1B
## CBLB ---> LATS1
## CBLB ---> ARID1B
## TERT ---> LATS1
## TERT ---> ARID1B
## CDKN2A ---> LATS1
## CDKN2A ---> ARID1B
## TP53 ---> DNM2
## FAT1 ---> DNM2
## SPEN ---> DNM2
## CBLB ---> DNM2
## TERT ---> DNM2
## CDKN2A ---> DNM2
## LATS1 ---> ASXL1
## ARID1B ---> ASXL1
## DNM2 ---> PTPRC
##
## Tree score 0.015625
##
## $phylogenies$CRUK0016$`9`
## [ ctree - ctree rank 9/13 for CRUK0016 ]
##
## # A tibble: 5 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 0.99 0.99
## 2 16 2 TRUE FALSE 0.97 0
## 3 10 1 TRUE FALSE 0.34 0.3
## 4 2 1 TRUE FALSE 0.53 0
## 5 6 1 TRUE FALSE 0.31 0.53
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53, FAT1, SPEN, CBLB, TERT, CDKN2A
## |-16 :: LATS1, ARID1B
## | |-10 :: DNM2
## | \-2 :: ASXL1
## \-6 :: PTPRC
##
## Information transfer
##
## GL ---> TP53
## GL ---> FAT1
## GL ---> SPEN
## GL ---> CBLB
## GL ---> TERT
## GL ---> CDKN2A
## TP53 ---> LATS1
## TP53 ---> ARID1B
## FAT1 ---> LATS1
## FAT1 ---> ARID1B
## SPEN ---> LATS1
## SPEN ---> ARID1B
## CBLB ---> LATS1
## CBLB ---> ARID1B
## TERT ---> LATS1
## TERT ---> ARID1B
## CDKN2A ---> LATS1
## CDKN2A ---> ARID1B
## LATS1 ---> DNM2
## ARID1B ---> DNM2
## LATS1 ---> ASXL1
## ARID1B ---> ASXL1
## TP53 ---> PTPRC
## FAT1 ---> PTPRC
## SPEN ---> PTPRC
## CBLB ---> PTPRC
## TERT ---> PTPRC
## CDKN2A ---> PTPRC
##
## Tree score 0.015625
##
## $phylogenies$CRUK0016$`10`
## [ ctree - ctree rank 10/13 for CRUK0016 ]
##
## # A tibble: 5 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 0.99 0.99
## 2 16 2 TRUE FALSE 0.97 0
## 3 10 1 TRUE FALSE 0.34 0.3
## 4 2 1 TRUE FALSE 0.53 0
## 5 6 1 TRUE FALSE 0.31 0.53
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53, FAT1, SPEN, CBLB, TERT, CDKN2A
## \-16 :: LATS1, ARID1B
## |-6 :: PTPRC
## | \-10 :: DNM2
## \-2 :: ASXL1
##
## Information transfer
##
## GL ---> TP53
## GL ---> FAT1
## GL ---> SPEN
## GL ---> CBLB
## GL ---> TERT
## GL ---> CDKN2A
## TP53 ---> LATS1
## TP53 ---> ARID1B
## FAT1 ---> LATS1
## FAT1 ---> ARID1B
## SPEN ---> LATS1
## SPEN ---> ARID1B
## CBLB ---> LATS1
## CBLB ---> ARID1B
## TERT ---> LATS1
## TERT ---> ARID1B
## CDKN2A ---> LATS1
## CDKN2A ---> ARID1B
## PTPRC ---> DNM2
## LATS1 ---> ASXL1
## ARID1B ---> ASXL1
## LATS1 ---> PTPRC
## ARID1B ---> PTPRC
##
## Tree score 0.015625
##
## $phylogenies$CRUK0016$`11`
## [ ctree - ctree rank 11/13 for CRUK0016 ]
##
## # A tibble: 5 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 0.99 0.99
## 2 16 2 TRUE FALSE 0.97 0
## 3 10 1 TRUE FALSE 0.34 0.3
## 4 2 1 TRUE FALSE 0.53 0
## 5 6 1 TRUE FALSE 0.31 0.53
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53, FAT1, SPEN, CBLB, TERT, CDKN2A
## |-6 :: PTPRC
## | \-10 :: DNM2
## \-16 :: LATS1, ARID1B
## \-2 :: ASXL1
##
## Information transfer
##
## GL ---> TP53
## GL ---> FAT1
## GL ---> SPEN
## GL ---> CBLB
## GL ---> TERT
## GL ---> CDKN2A
## TP53 ---> LATS1
## TP53 ---> ARID1B
## FAT1 ---> LATS1
## FAT1 ---> ARID1B
## SPEN ---> LATS1
## SPEN ---> ARID1B
## CBLB ---> LATS1
## CBLB ---> ARID1B
## TERT ---> LATS1
## TERT ---> ARID1B
## CDKN2A ---> LATS1
## CDKN2A ---> ARID1B
## PTPRC ---> DNM2
## LATS1 ---> ASXL1
## ARID1B ---> ASXL1
## TP53 ---> PTPRC
## FAT1 ---> PTPRC
## SPEN ---> PTPRC
## CBLB ---> PTPRC
## TERT ---> PTPRC
## CDKN2A ---> PTPRC
##
## Tree score 0.015625
##
## $phylogenies$CRUK0016$`12`
## [ ctree - ctree rank 12/13 for CRUK0016 ]
##
## # A tibble: 5 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 0.99 0.99
## 2 16 2 TRUE FALSE 0.97 0
## 3 10 1 TRUE FALSE 0.34 0.3
## 4 2 1 TRUE FALSE 0.53 0
## 5 6 1 TRUE FALSE 0.31 0.53
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53, FAT1, SPEN, CBLB, TERT, CDKN2A
## \-16 :: LATS1, ARID1B
## |-2 :: ASXL1
## | \-6 :: PTPRC
## \-10 :: DNM2
##
## Information transfer
##
## GL ---> TP53
## GL ---> FAT1
## GL ---> SPEN
## GL ---> CBLB
## GL ---> TERT
## GL ---> CDKN2A
## TP53 ---> LATS1
## TP53 ---> ARID1B
## FAT1 ---> LATS1
## FAT1 ---> ARID1B
## SPEN ---> LATS1
## SPEN ---> ARID1B
## CBLB ---> LATS1
## CBLB ---> ARID1B
## TERT ---> LATS1
## TERT ---> ARID1B
## CDKN2A ---> LATS1
## CDKN2A ---> ARID1B
## LATS1 ---> DNM2
## ARID1B ---> DNM2
## LATS1 ---> ASXL1
## ARID1B ---> ASXL1
## ASXL1 ---> PTPRC
##
## Tree score 0.015625
##
## $phylogenies$CRUK0016$`13`
## [ ctree - ctree rank 13/13 for CRUK0016 ]
##
## # A tibble: 5 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 0.99 0.99
## 2 16 2 TRUE FALSE 0.97 0
## 3 10 1 TRUE FALSE 0.34 0.3
## 4 2 1 TRUE FALSE 0.53 0
## 5 6 1 TRUE FALSE 0.31 0.53
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53, FAT1, SPEN, CBLB, TERT, CDKN2A
## |-16 :: LATS1, ARID1B
## | \-2 :: ASXL1
## | \-6 :: PTPRC
## \-10 :: DNM2
##
## Information transfer
##
## GL ---> TP53
## GL ---> FAT1
## GL ---> SPEN
## GL ---> CBLB
## GL ---> TERT
## GL ---> CDKN2A
## TP53 ---> LATS1
## TP53 ---> ARID1B
## FAT1 ---> LATS1
## FAT1 ---> ARID1B
## SPEN ---> LATS1
## SPEN ---> ARID1B
## CBLB ---> LATS1
## CBLB ---> ARID1B
## TERT ---> LATS1
## TERT ---> ARID1B
## CDKN2A ---> LATS1
## CDKN2A ---> ARID1B
## TP53 ---> DNM2
## FAT1 ---> DNM2
## SPEN ---> DNM2
## CBLB ---> DNM2
## TERT ---> DNM2
## CDKN2A ---> DNM2
## LATS1 ---> ASXL1
## ARID1B ---> ASXL1
## ASXL1 ---> PTPRC
##
## Tree score 0.015625
##
##
## $phylogenies$CRUK0017
## $phylogenies$CRUK0017$`1`
## [ ctree - ctree rank 1/1 for CRUK0017 ]
##
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 1 1 1 1
## 2 3 1 TRUE FALSE 0 0.94 0.95 0.59
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1] :: TP53, ARID1B, ARID2, KEAP1, MYC
## \-3 :: KRAS
##
## Information transfer
##
## GL ---> TP53
## GL ---> ARID1B
## GL ---> ARID2
## GL ---> KEAP1
## GL ---> MYC
## TP53 ---> KRAS
## ARID1B ---> KRAS
## ARID2 ---> KRAS
## KEAP1 ---> KRAS
## MYC ---> KRAS
##
## Tree score 1
##
##
## $phylogenies$CRUK0018
## $phylogenies$CRUK0018$`1`
## [ ctree - ctree rank 1/1 for CRUK0018 ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: CMTR2, KRAS, MGA, COL5A2
##
## Information transfer
##
## GL ---> CMTR2
## GL ---> KRAS
## GL ---> MGA
## GL ---> COL5A2
##
## Tree score 1
##
##
## $phylogenies$CRUK0019
## $phylogenies$CRUK0019$`1`
## [ ctree - ctree rank 1/1 for CRUK0019 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.97 0.96
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: EGFR
##
## Information transfer
##
## GL ---> EGFR
##
## Tree score 1
##
##
## $phylogenies$CRUK0020
## $phylogenies$CRUK0020$`1`
## [ ctree - ctree rank 1/2 for CRUK0020 ]
##
## # A tibble: 4 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 7 TRUE TRUE 1 1
## 2 2 1 TRUE FALSE 0.87 0
## 3 3 1 TRUE FALSE 0.9 0.08
## 4 4 1 TRUE FALSE 0 0.85
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: KEAP1, TP53, MGA, ARID2, COL2A1, PRF1, KRAS
## |-3 :: BAP1
## | \-2 :: PIK3CA
## \-4 :: NCOR1
##
## Information transfer
##
## GL ---> KEAP1
## GL ---> TP53
## GL ---> MGA
## GL ---> ARID2
## GL ---> COL2A1
## GL ---> PRF1
## GL ---> KRAS
## BAP1 ---> PIK3CA
## KEAP1 ---> BAP1
## TP53 ---> BAP1
## MGA ---> BAP1
## ARID2 ---> BAP1
## COL2A1 ---> BAP1
## PRF1 ---> BAP1
## KRAS ---> BAP1
## KEAP1 ---> NCOR1
## TP53 ---> NCOR1
## MGA ---> NCOR1
## ARID2 ---> NCOR1
## COL2A1 ---> NCOR1
## PRF1 ---> NCOR1
## KRAS ---> NCOR1
##
## Tree score 0.666666666666667
##
## $phylogenies$CRUK0020$`2`
## [ ctree - ctree rank 2/2 for CRUK0020 ]
##
## # A tibble: 4 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 7 TRUE TRUE 1 1
## 2 2 1 TRUE FALSE 0.87 0
## 3 3 1 TRUE FALSE 0.9 0.08
## 4 4 1 TRUE FALSE 0 0.85
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: KEAP1, TP53, MGA, ARID2, COL2A1, PRF1, KRAS
## \-4 :: NCOR1
## \-3 :: BAP1
## \-2 :: PIK3CA
##
## Information transfer
##
## GL ---> KEAP1
## GL ---> TP53
## GL ---> MGA
## GL ---> ARID2
## GL ---> COL2A1
## GL ---> PRF1
## GL ---> KRAS
## BAP1 ---> PIK3CA
## NCOR1 ---> BAP1
## KEAP1 ---> NCOR1
## TP53 ---> NCOR1
## MGA ---> NCOR1
## ARID2 ---> NCOR1
## COL2A1 ---> NCOR1
## PRF1 ---> NCOR1
## KRAS ---> NCOR1
##
## Tree score 0.166666666666667
##
##
## $phylogenies$CRUK0021
## $phylogenies$CRUK0021$`1`
## [ ctree - ctree rank 1/1 for CRUK0021 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: EGFR, TP53, CHEK2, CDKN2A
##
## Information transfer
##
## GL ---> EGFR
## GL ---> TP53
## GL ---> CHEK2
## GL ---> CDKN2A
##
## Tree score 1
##
##
## $phylogenies$CRUK0022
## $phylogenies$CRUK0022$`1`
## [ ctree - ctree rank 1/1 for CRUK0022 ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.99 0.99
## 2 2 1 TRUE FALSE 0.85 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R2] :: TP53, EGFR
## \-2 :: CIC
##
## Information transfer
##
## GL ---> TP53
## GL ---> EGFR
## TP53 ---> CIC
## EGFR ---> CIC
##
## Tree score 1
##
##
## $phylogenies$CRUK0023
## $phylogenies$CRUK0023$`1`
## [ ctree - ctree rank 1/1 for CRUK0023 ]
##
## # A tibble: 3 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.99 0.98 0.99 0.95
## 2 4 2 TRUE FALSE 0.01 0.945 0 0
## 3 2 1 TRUE FALSE 0.81 0 0 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R3, R4] :: WRN, KRAS, CDKN2A
## |-2 :: TP53
## \-4 :: PTPRC, KMT2D
##
## Information transfer
##
## GL ---> WRN
## GL ---> KRAS
## GL ---> CDKN2A
## WRN ---> PTPRC
## WRN ---> KMT2D
## KRAS ---> PTPRC
## KRAS ---> KMT2D
## CDKN2A ---> PTPRC
## CDKN2A ---> KMT2D
## WRN ---> TP53
## KRAS ---> TP53
## CDKN2A ---> TP53
##
## Tree score 1
##
##
## $phylogenies$CRUK0024
## $phylogenies$CRUK0024$`1`
## [ ctree - ctree rank 1/1 for CRUK0024 ]
##
## # A tibble: 3 x 8
## cluster nMuts is.driver is.clonal R1 R3 R4 R6
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1
## 2 3 1 TRUE FALSE 0.88 0.97 0.95 0
## 3 4 1 TRUE FALSE 0.83 0 0 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R6] :: TP53, STK11, POLE, EGFR
## \-3 :: ATM
## \-4 :: NCOR1
##
## Information transfer
##
## GL ---> TP53
## GL ---> STK11
## GL ---> POLE
## GL ---> EGFR
## TP53 ---> ATM
## STK11 ---> ATM
## POLE ---> ATM
## EGFR ---> ATM
## ATM ---> NCOR1
##
## Tree score 1
##
##
## $phylogenies$CRUK0025
## $phylogenies$CRUK0025$`1`
## [ ctree - ctree rank 1/1 for CRUK0025 ]
##
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3] :: KRAS, TP53, MGA
##
## Information transfer
##
## GL ---> KRAS
## GL ---> TP53
## GL ---> MGA
##
## Tree score 1
##
##
## $phylogenies$CRUK0026
## $phylogenies$CRUK0026$`1`
## [ ctree - ctree rank 1/1 for CRUK0026 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 0.98 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: TP53, EGFR, RB1, SERPINB13
##
## Information transfer
##
## GL ---> TP53
## GL ---> EGFR
## GL ---> RB1
## GL ---> SERPINB13
##
## Tree score 1
##
##
## $phylogenies$CRUK0027
## $phylogenies$CRUK0027$`1`
## [ ctree - ctree rank 1/1 for CRUK0027 ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.96 1
## 2 2 1 TRUE FALSE 0 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1] :: KRAS, TP53
## \-2 :: PLXNB2
##
## Information transfer
##
## GL ---> KRAS
## GL ---> TP53
## KRAS ---> PLXNB2
## TP53 ---> PLXNB2
##
## Tree score 1
##
##
## $phylogenies$CRUK0028
## $phylogenies$CRUK0028$`1`
## [ ctree - ctree rank 1/1 for CRUK0028 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.975 0.95
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: APC, EGFR
##
## Information transfer
##
## GL ---> APC
## GL ---> EGFR
##
## Tree score 1
##
##
## $phylogenies$CRUK0029
## $phylogenies$CRUK0029$`1`
## [ ctree - ctree rank 1/1 for CRUK0029 ]
##
## # A tibble: 1 x 10
## cluster nMuts is.driver is.clonal R2 R4 R5 R6 R7 R8
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 0.99 0.98 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R2, R4, R5, R6, R7, R8] :: TP53, NRAS, MGA, CCND1
##
## Information transfer
##
## GL ---> TP53
## GL ---> NRAS
## GL ---> MGA
## GL ---> CCND1
##
## Tree score 1
##
##
## $phylogenies$CRUK0030
## $phylogenies$CRUK0030$`1`
## [ ctree - ctree rank 1/1 for CRUK0030 ]
##
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 1 0.98 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3] :: KRAS, TSC2, U2AF1, TP53, FBXW7, NF1
##
## Information transfer
##
## GL ---> KRAS
## GL ---> TSC2
## GL ---> U2AF1
## GL ---> TP53
## GL ---> FBXW7
## GL ---> NF1
##
## Tree score 1
##
##
## $phylogenies$CRUK0031
## $phylogenies$CRUK0031$`1`
## [ ctree - ctree rank 1/1 for CRUK0031 ]
##
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1
## 2 6 1 TRUE FALSE 0.88 0.05 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R3] :: KEAP1, CDKN2A, PRF1, FGFR1
## \-6 :: NF1
##
## Information transfer
##
## GL ---> KEAP1
## GL ---> CDKN2A
## GL ---> PRF1
## GL ---> FGFR1
## KEAP1 ---> NF1
## CDKN2A ---> NF1
## PRF1 ---> NF1
## FGFR1 ---> NF1
##
## Tree score 1
##
##
## $phylogenies$CRUK0032
## $phylogenies$CRUK0032$`1`
## [ ctree - ctree rank 1/1 for CRUK0032 ]
##
## # A tibble: 3 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1
## 2 4 1 TRUE FALSE 0 0.97 0 0.98
## 3 6 1 TRUE FALSE 0 0 0 0.3
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R3] :: ATM, RAD21, U2AF1, RNF43
## \-4 :: CCND1
## \-6 :: ARID1B
##
## Information transfer
##
## GL ---> ATM
## GL ---> RAD21
## GL ---> U2AF1
## GL ---> RNF43
## ATM ---> CCND1
## RAD21 ---> CCND1
## U2AF1 ---> CCND1
## RNF43 ---> CCND1
## CCND1 ---> ARID1B
##
## Tree score 1
##
##
## $phylogenies$CRUK0033
## $phylogenies$CRUK0033$`1`
## [ ctree - ctree rank 1/1 for CRUK0033 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.99 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: KEAP1, CTNNB1
##
## Information transfer
##
## GL ---> KEAP1
## GL ---> CTNNB1
##
## Tree score 1
##
##
## $phylogenies$CRUK0034
## $phylogenies$CRUK0034$`1`
## [ ctree - ctree rank 1/1 for CRUK0034 ]
##
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 1 1 1
## 2 4 1 TRUE FALSE 0 0.5 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R3] :: ATM, KRAS, PLXNB2
## \-4 :: MGA
##
## Information transfer
##
## GL ---> ATM
## GL ---> KRAS
## GL ---> PLXNB2
## ATM ---> MGA
## KRAS ---> MGA
## PLXNB2 ---> MGA
##
## Tree score 1
##
##
## $phylogenies$CRUK0035
## $phylogenies$CRUK0035$`1`
## [ ctree - ctree rank 1/1 for CRUK0035 ]
##
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal LN1 R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.98 0.98 0.99 0.99
## 2 4 1 TRUE FALSE 0 0.8 0 0.01
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [LN1, R2] :: TP53, FAS
## \-4 :: FLT4
##
## Information transfer
##
## GL ---> TP53
## GL ---> FAS
## TP53 ---> FLT4
## FAS ---> FLT4
##
## Tree score 1
##
##
## $phylogenies$CRUK0036
## $phylogenies$CRUK0036$`1`
## [ ctree - ctree rank 1/1 for CRUK0036 ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 0.99 0.98 0.97 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: KRAS, PIK3CA, KEAP1, ARHGAP35, TERT
##
## Information transfer
##
## GL ---> KRAS
## GL ---> PIK3CA
## GL ---> KEAP1
## GL ---> ARHGAP35
## GL ---> TERT
##
## Tree score 1
##
##
## $phylogenies$CRUK0037
## $phylogenies$CRUK0037$`1`
## [ ctree - ctree rank 1/1 for CRUK0037 ]
##
## # A tibble: 1 x 9
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.99 1 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4, R5] :: NCOA6, CREBBP, KRAS
##
## Information transfer
##
## GL ---> NCOA6
## GL ---> CREBBP
## GL ---> KRAS
##
## Tree score 1
##
##
## $phylogenies$CRUK0038
## $phylogenies$CRUK0038$`1`
## [ ctree - ctree rank 1/1 for CRUK0038 ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.99
## 2 3 1 TRUE FALSE 0 0.38
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1] :: KRAS
## \-3 :: KMT2D
##
## Information transfer
##
## GL ---> KRAS
## KRAS ---> KMT2D
##
## Tree score 1
##
##
## $phylogenies$CRUK0039
## $phylogenies$CRUK0039$`1`
## [ ctree - ctree rank 1/1 for CRUK0039 ]
##
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3] :: KRAS, CMTR2, NF1, PHOX2B
##
## Information transfer
##
## GL ---> KRAS
## GL ---> CMTR2
## GL ---> NF1
## GL ---> PHOX2B
##
## Tree score 1
##
##
## $phylogenies$CRUK0040
## $phylogenies$CRUK0040$`1`
## [ ctree - ctree rank 1/1 for CRUK0040 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 0.99 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: NCOR1, RAD21, KRAS, GATA3
##
## Information transfer
##
## GL ---> NCOR1
## GL ---> RAD21
## GL ---> KRAS
## GL ---> GATA3
##
## Tree score 1
##
##
## $phylogenies$CRUK0041
## $phylogenies$CRUK0041$`1`
## [ ctree - ctree rank 1/1 for CRUK0041 ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.98 0.99 0.99 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: BRAF, TERT, EGFR
##
## Information transfer
##
## GL ---> BRAF
## GL ---> TERT
## GL ---> EGFR
##
## Tree score 1
##
##
## $phylogenies$CRUK0042
## $phylogenies$CRUK0042$`1`
## [ ctree - ctree rank 1/1 for CRUK0042 ]
##
## # A tibble: 1 x 5
## cluster nMuts is.driver is.clonal R1
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 1 TRUE TRUE 0.91
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1] :: KRAS
##
## Information transfer
##
## GL ---> KRAS
##
## Tree score 1
##
##
## $phylogenies$CRUK0043
## $phylogenies$CRUK0043$`1`
## [ ctree - ctree rank 1/1 for CRUK0043 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: MET
##
## Information transfer
##
## GL ---> MET
##
## Tree score 1
##
##
## $phylogenies$CRUK0044
## $phylogenies$CRUK0044$`1`
## [ ctree - ctree rank 1/1 for CRUK0044 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: KRAS
##
## Information transfer
##
## GL ---> KRAS
##
## Tree score 1
##
##
## $phylogenies$CRUK0045
## $phylogenies$CRUK0045$`1`
## [ ctree - ctree rank 1/1 for CRUK0045 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.98 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R3] :: BAP1
##
## Information transfer
##
## GL ---> BAP1
##
## Tree score 1
##
##
## $phylogenies$CRUK0046
## $phylogenies$CRUK0046$`1`
## [ ctree - ctree rank 1/1 for CRUK0046 ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 1 0.98 0.995 0.96
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: KEAP1, APC
##
## Information transfer
##
## GL ---> KEAP1
## GL ---> APC
##
## Tree score 1
##
##
## $phylogenies$CRUK0047
## $phylogenies$CRUK0047$`1`
## [ ctree - ctree rank 1/1 for CRUK0047 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 0.99 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: STK11, APC, KRAS, MYC
##
## Information transfer
##
## GL ---> STK11
## GL ---> APC
## GL ---> KRAS
## GL ---> MYC
##
## Tree score 1
##
##
## $phylogenies$CRUK0048
## $phylogenies$CRUK0048$`1`
## [ ctree - ctree rank 1/1 for CRUK0048 ]
##
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 7 TRUE TRUE 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3] :: APC, PRDM1, ARHGAP35, TP53, BRAF, EGFR, MYC
##
## Information transfer
##
## GL ---> APC
## GL ---> PRDM1
## GL ---> ARHGAP35
## GL ---> TP53
## GL ---> BRAF
## GL ---> EGFR
## GL ---> MYC
##
## Tree score 1
##
##
## $phylogenies$CRUK0049
## $phylogenies$CRUK0049$`1`
## [ ctree - ctree rank 1/1 for CRUK0049 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: RB1, TP53, COL2A1, EGFR, KRAS
##
## Information transfer
##
## GL ---> RB1
## GL ---> TP53
## GL ---> COL2A1
## GL ---> EGFR
## GL ---> KRAS
##
## Tree score 1
##
##
## $phylogenies$CRUK0050
## $phylogenies$CRUK0050$`1`
## [ ctree - ctree rank 1/1 for CRUK0050 ]
##
## # A tibble: 1 x 9
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.99 0.99 0.99 1 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4, R5] :: KRAS, STK11, MYC
##
## Information transfer
##
## GL ---> KRAS
## GL ---> STK11
## GL ---> MYC
##
## Tree score 1
##
##
## $phylogenies$CRUK0051
## $phylogenies$CRUK0051$`1`
## [ ctree - ctree rank 1/1 for CRUK0051 ]
##
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1
## 2 3 1 TRUE FALSE 0.97 0 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R3, R4] :: KRAS, FBXW7, TP53, EGFR
## \-3 :: EP300
##
## Information transfer
##
## GL ---> KRAS
## GL ---> FBXW7
## GL ---> TP53
## GL ---> EGFR
## KRAS ---> EP300
## FBXW7 ---> EP300
## TP53 ---> EP300
## EGFR ---> EP300
##
## Tree score 1
##
##
## $phylogenies$CRUK0052
## $phylogenies$CRUK0052$`1`
## [ ctree - ctree rank 1/1 for CRUK0052 ]
##
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R1 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 8 TRUE TRUE 1 1 1
## 2 2 1 TRUE FALSE 0 0 0.86
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R3] :: KMT2D, KRAS, NOTCH2, MGA, KEAP1, TP53, NF1, SGK223
## \-2 :: UBR5
##
## Information transfer
##
## GL ---> KMT2D
## GL ---> KRAS
## GL ---> NOTCH2
## GL ---> MGA
## GL ---> KEAP1
## GL ---> TP53
## GL ---> NF1
## GL ---> SGK223
## KMT2D ---> UBR5
## KRAS ---> UBR5
## NOTCH2 ---> UBR5
## MGA ---> UBR5
## KEAP1 ---> UBR5
## TP53 ---> UBR5
## NF1 ---> UBR5
## SGK223 ---> UBR5
##
## Tree score 1
##
##
## $phylogenies$CRUK0054
## $phylogenies$CRUK0054$`1`
## [ ctree - ctree rank 1/1 for CRUK0054 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: EGFR
##
## Information transfer
##
## GL ---> EGFR
##
## Tree score 1
##
##
## $phylogenies$CRUK0055
## $phylogenies$CRUK0055$`1`
## [ ctree - ctree rank 1/1 for CRUK0055 ]
##
## # A tibble: 2 x 5
## cluster nMuts is.driver is.clonal R2
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 2 TRUE TRUE 1
## 2 2 1 TRUE FALSE 0.32
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: FANCM, UBR5
## \-2 :: FAT1
##
## Information transfer
##
## GL ---> FANCM
## GL ---> UBR5
## FANCM ---> FAT1
## UBR5 ---> FAT1
##
## Tree score 1
##
##
## $phylogenies$CRUK0056
## $phylogenies$CRUK0056$`1`
## [ ctree - ctree rank 1/1 for CRUK0056 ]
##
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 1 1 1
## 2 3 1 TRUE FALSE 0 0.12 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1] :: RASA1, CREBBP
## \-3 :: TP53
##
## Information transfer
##
## GL ---> RASA1
## GL ---> CREBBP
## RASA1 ---> TP53
## CREBBP ---> TP53
##
## Tree score 1
##
##
## $phylogenies$CRUK0057
## $phylogenies$CRUK0057$`1`
## [ ctree - ctree rank 1/1 for CRUK0057 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: KRAS, SMARCA4, TSC2, DNM2, TERT
##
## Information transfer
##
## GL ---> KRAS
## GL ---> SMARCA4
## GL ---> TSC2
## GL ---> DNM2
## GL ---> TERT
##
## Tree score 1
##
##
## $phylogenies$CRUK0058
## $phylogenies$CRUK0058$`1`
## [ ctree - ctree rank 1/1 for CRUK0058 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.98 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: TP53, EGFR
##
## Information transfer
##
## GL ---> TP53
## GL ---> EGFR
##
## Tree score 1
##
##
## $phylogenies$CRUK0059
## $phylogenies$CRUK0059$`1`
## [ ctree - ctree rank 1/1 for CRUK0059 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: KRAS
##
## Information transfer
##
## GL ---> KRAS
##
## Tree score 1
##
##
## $phylogenies$CRUK0060
## $phylogenies$CRUK0060$`1`
## [ ctree - ctree rank 1/1 for CRUK0060 ]
##
## # A tibble: 1 x 5
## cluster nMuts is.driver is.clonal R1
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 11 TRUE TRUE 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1] :: SERPINB13, ARID2, COL5A2, FANCM, PHOX2B, COL2A1, RASA1, NF1, NCOA6, NOTCH2, KMT2C
##
## Information transfer
##
## GL ---> SERPINB13
## GL ---> ARID2
## GL ---> COL5A2
## GL ---> FANCM
## GL ---> PHOX2B
## GL ---> COL2A1
## GL ---> RASA1
## GL ---> NF1
## GL ---> NCOA6
## GL ---> NOTCH2
## GL ---> KMT2C
##
## Tree score 1
##
##
## $phylogenies$CRUK0061
## $phylogenies$CRUK0061$`1`
## [ ctree - ctree rank 1/1 for CRUK0061 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: STK11
##
## Information transfer
##
## GL ---> STK11
##
## Tree score 1
##
##
## $phylogenies$CRUK0062
## $phylogenies$CRUK0062$`1`
## [ ctree - ctree rank 1/2 for CRUK0062 ]
##
## # A tibble: 4 x 11
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5 R6
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 4 4 TRUE TRUE 0.99 0.99 0.98 0.97 0.99 0.99
## 2 1 1 TRUE FALSE 0 0.01 0 0 0 0.94
## 3 16 1 TRUE FALSE 0.93 0.86 0.08 0.02 0.12 0
## 4 2 1 TRUE FALSE 0.84 0.83 0.02 0 0 0
## # … with 1 more variable: R7 <dbl>
##
## Tree shape (drivers annotated)
##
## \-GL
## \-4 :: TP53, PIK3CA, SOX2, CCND1
## |-16 :: UBR5
## | \-2 :: PLXNB2
## \-1 :: FAS
##
## Information transfer
##
## GL ---> TP53
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> CCND1
## TP53 ---> FAS
## PIK3CA ---> FAS
## SOX2 ---> FAS
## CCND1 ---> FAS
## TP53 ---> UBR5
## PIK3CA ---> UBR5
## SOX2 ---> UBR5
## CCND1 ---> UBR5
## UBR5 ---> PLXNB2
##
## Tree score 0.75
##
## $phylogenies$CRUK0062$`2`
## [ ctree - ctree rank 2/2 for CRUK0062 ]
##
## # A tibble: 4 x 11
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5 R6
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 4 4 TRUE TRUE 0.99 0.99 0.98 0.97 0.99 0.99
## 2 1 1 TRUE FALSE 0 0.01 0 0 0 0.94
## 3 16 1 TRUE FALSE 0.93 0.86 0.08 0.02 0.12 0
## 4 2 1 TRUE FALSE 0.84 0.83 0.02 0 0 0
## # … with 1 more variable: R7 <dbl>
##
## Tree shape (drivers annotated)
##
## \-GL
## \-4 :: TP53, PIK3CA, SOX2, CCND1
## |-2 :: PLXNB2
## |-16 :: UBR5
## \-1 :: FAS
##
## Information transfer
##
## GL ---> TP53
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> CCND1
## TP53 ---> FAS
## PIK3CA ---> FAS
## SOX2 ---> FAS
## CCND1 ---> FAS
## TP53 ---> UBR5
## PIK3CA ---> UBR5
## SOX2 ---> UBR5
## CCND1 ---> UBR5
## TP53 ---> PLXNB2
## PIK3CA ---> PLXNB2
## SOX2 ---> PLXNB2
## CCND1 ---> PLXNB2
##
## Tree score 0.178571428571429
##
##
## $phylogenies$CRUK0063
## $phylogenies$CRUK0063$`1`
## [ ctree - ctree rank 1/6 for CRUK0063 ]
##
## # A tibble: 4 x 9
## cluster nMuts is.driver is.clonal R3 R4 R5 R6 R7
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2 7 TRUE TRUE 0.93 0.99 0.99 0.99 1
## 2 1 2 TRUE FALSE 0 0.99 0.99 0.98 1
## 3 10 1 TRUE FALSE 0 0.99 0.99 0.98 1
## 4 6 1 TRUE FALSE 0 0.02 0.7 0.36 0.55
##
## Tree shape (drivers annotated)
##
## \-GL
## \-2 [R3] :: PIK3CA, TP53, FBXW7, CDKN2A, SOX2, TERT, PRF1
## \-10 :: EP300
## \-1 :: NF1, CYLD
## \-6 :: FANCM
##
## Information transfer
##
## GL ---> PIK3CA
## GL ---> TP53
## GL ---> FBXW7
## GL ---> CDKN2A
## GL ---> SOX2
## GL ---> TERT
## GL ---> PRF1
## EP300 ---> NF1
## EP300 ---> CYLD
## PIK3CA ---> EP300
## TP53 ---> EP300
## FBXW7 ---> EP300
## CDKN2A ---> EP300
## SOX2 ---> EP300
## TERT ---> EP300
## PRF1 ---> EP300
## NF1 ---> FANCM
## CYLD ---> FANCM
##
## Tree score 0.125
##
## $phylogenies$CRUK0063$`2`
## [ ctree - ctree rank 2/6 for CRUK0063 ]
##
## # A tibble: 4 x 9
## cluster nMuts is.driver is.clonal R3 R4 R5 R6 R7
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2 7 TRUE TRUE 0.93 0.99 0.99 0.99 1
## 2 1 2 TRUE FALSE 0 0.99 0.99 0.98 1
## 3 10 1 TRUE FALSE 0 0.99 0.99 0.98 1
## 4 6 1 TRUE FALSE 0 0.02 0.7 0.36 0.55
##
## Tree shape (drivers annotated)
##
## \-GL
## \-2 [R3] :: PIK3CA, TP53, FBXW7, CDKN2A, SOX2, TERT, PRF1
## \-1 :: NF1, CYLD
## \-10 :: EP300
## \-6 :: FANCM
##
## Information transfer
##
## GL ---> PIK3CA
## GL ---> TP53
## GL ---> FBXW7
## GL ---> CDKN2A
## GL ---> SOX2
## GL ---> TERT
## GL ---> PRF1
## PIK3CA ---> NF1
## PIK3CA ---> CYLD
## TP53 ---> NF1
## TP53 ---> CYLD
## FBXW7 ---> NF1
## FBXW7 ---> CYLD
## CDKN2A ---> NF1
## CDKN2A ---> CYLD
## SOX2 ---> NF1
## SOX2 ---> CYLD
## TERT ---> NF1
## TERT ---> CYLD
## PRF1 ---> NF1
## PRF1 ---> CYLD
## NF1 ---> EP300
## CYLD ---> EP300
## EP300 ---> FANCM
##
## Tree score 0.125
##
## $phylogenies$CRUK0063$`3`
## [ ctree - ctree rank 3/6 for CRUK0063 ]
##
## # A tibble: 4 x 9
## cluster nMuts is.driver is.clonal R3 R4 R5 R6 R7
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2 7 TRUE TRUE 0.93 0.99 0.99 0.99 1
## 2 1 2 TRUE FALSE 0 0.99 0.99 0.98 1
## 3 10 1 TRUE FALSE 0 0.99 0.99 0.98 1
## 4 6 1 TRUE FALSE 0 0.02 0.7 0.36 0.55
##
## Tree shape (drivers annotated)
##
## \-GL
## \-2 [R3] :: PIK3CA, TP53, FBXW7, CDKN2A, SOX2, TERT, PRF1
## \-10 :: EP300
## |-1 :: NF1, CYLD
## \-6 :: FANCM
##
## Information transfer
##
## GL ---> PIK3CA
## GL ---> TP53
## GL ---> FBXW7
## GL ---> CDKN2A
## GL ---> SOX2
## GL ---> TERT
## GL ---> PRF1
## EP300 ---> NF1
## EP300 ---> CYLD
## PIK3CA ---> EP300
## TP53 ---> EP300
## FBXW7 ---> EP300
## CDKN2A ---> EP300
## SOX2 ---> EP300
## TERT ---> EP300
## PRF1 ---> EP300
## EP300 ---> FANCM
##
## Tree score 0.025
##
## $phylogenies$CRUK0063$`4`
## [ ctree - ctree rank 4/6 for CRUK0063 ]
##
## # A tibble: 4 x 9
## cluster nMuts is.driver is.clonal R3 R4 R5 R6 R7
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2 7 TRUE TRUE 0.93 0.99 0.99 0.99 1
## 2 1 2 TRUE FALSE 0 0.99 0.99 0.98 1
## 3 10 1 TRUE FALSE 0 0.99 0.99 0.98 1
## 4 6 1 TRUE FALSE 0 0.02 0.7 0.36 0.55
##
## Tree shape (drivers annotated)
##
## \-GL
## \-2 [R3] :: PIK3CA, TP53, FBXW7, CDKN2A, SOX2, TERT, PRF1
## \-1 :: NF1, CYLD
## |-10 :: EP300
## \-6 :: FANCM
##
## Information transfer
##
## GL ---> PIK3CA
## GL ---> TP53
## GL ---> FBXW7
## GL ---> CDKN2A
## GL ---> SOX2
## GL ---> TERT
## GL ---> PRF1
## PIK3CA ---> NF1
## PIK3CA ---> CYLD
## TP53 ---> NF1
## TP53 ---> CYLD
## FBXW7 ---> NF1
## FBXW7 ---> CYLD
## CDKN2A ---> NF1
## CDKN2A ---> CYLD
## SOX2 ---> NF1
## SOX2 ---> CYLD
## TERT ---> NF1
## TERT ---> CYLD
## PRF1 ---> NF1
## PRF1 ---> CYLD
## NF1 ---> EP300
## CYLD ---> EP300
## NF1 ---> FANCM
## CYLD ---> FANCM
##
## Tree score 0.025
##
## $phylogenies$CRUK0063$`5`
## [ ctree - ctree rank 5/6 for CRUK0063 ]
##
## # A tibble: 4 x 9
## cluster nMuts is.driver is.clonal R3 R4 R5 R6 R7
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2 7 TRUE TRUE 0.93 0.99 0.99 0.99 1
## 2 1 2 TRUE FALSE 0 0.99 0.99 0.98 1
## 3 10 1 TRUE FALSE 0 0.99 0.99 0.98 1
## 4 6 1 TRUE FALSE 0 0.02 0.7 0.36 0.55
##
## Tree shape (drivers annotated)
##
## \-GL
## \-2 [R3] :: PIK3CA, TP53, FBXW7, CDKN2A, SOX2, TERT, PRF1
## |-1 :: NF1, CYLD
## | \-6 :: FANCM
## \-10 :: EP300
##
## Information transfer
##
## GL ---> PIK3CA
## GL ---> TP53
## GL ---> FBXW7
## GL ---> CDKN2A
## GL ---> SOX2
## GL ---> TERT
## GL ---> PRF1
## PIK3CA ---> NF1
## PIK3CA ---> CYLD
## TP53 ---> NF1
## TP53 ---> CYLD
## FBXW7 ---> NF1
## FBXW7 ---> CYLD
## CDKN2A ---> NF1
## CDKN2A ---> CYLD
## SOX2 ---> NF1
## SOX2 ---> CYLD
## TERT ---> NF1
## TERT ---> CYLD
## PRF1 ---> NF1
## PRF1 ---> CYLD
## PIK3CA ---> EP300
## TP53 ---> EP300
## FBXW7 ---> EP300
## CDKN2A ---> EP300
## SOX2 ---> EP300
## TERT ---> EP300
## PRF1 ---> EP300
## NF1 ---> FANCM
## CYLD ---> FANCM
##
## Tree score 0.025
##
## $phylogenies$CRUK0063$`6`
## [ ctree - ctree rank 6/6 for CRUK0063 ]
##
## # A tibble: 4 x 9
## cluster nMuts is.driver is.clonal R3 R4 R5 R6 R7
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2 7 TRUE TRUE 0.93 0.99 0.99 0.99 1
## 2 1 2 TRUE FALSE 0 0.99 0.99 0.98 1
## 3 10 1 TRUE FALSE 0 0.99 0.99 0.98 1
## 4 6 1 TRUE FALSE 0 0.02 0.7 0.36 0.55
##
## Tree shape (drivers annotated)
##
## \-GL
## \-2 [R3] :: PIK3CA, TP53, FBXW7, CDKN2A, SOX2, TERT, PRF1
## |-10 :: EP300
## | \-6 :: FANCM
## \-1 :: NF1, CYLD
##
## Information transfer
##
## GL ---> PIK3CA
## GL ---> TP53
## GL ---> FBXW7
## GL ---> CDKN2A
## GL ---> SOX2
## GL ---> TERT
## GL ---> PRF1
## PIK3CA ---> NF1
## PIK3CA ---> CYLD
## TP53 ---> NF1
## TP53 ---> CYLD
## FBXW7 ---> NF1
## FBXW7 ---> CYLD
## CDKN2A ---> NF1
## CDKN2A ---> CYLD
## SOX2 ---> NF1
## SOX2 ---> CYLD
## TERT ---> NF1
## TERT ---> CYLD
## PRF1 ---> NF1
## PRF1 ---> CYLD
## PIK3CA ---> EP300
## TP53 ---> EP300
## FBXW7 ---> EP300
## CDKN2A ---> EP300
## SOX2 ---> EP300
## TERT ---> EP300
## PRF1 ---> EP300
## EP300 ---> FANCM
##
## Tree score 0.025
##
##
## $phylogenies$CRUK0064
## $phylogenies$CRUK0064$`1`
## [ ctree - ctree rank 1/1 for CRUK0064 ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 2 2 TRUE FALSE 0.64 0.11
## 2 1 1 TRUE TRUE 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53
## \-2 :: MLH1, FAT1
##
## Information transfer
##
## TP53 ---> MLH1
## TP53 ---> FAT1
## GL ---> TP53
##
## Tree score 1
##
##
## $phylogenies$CRUK0065
## $phylogenies$CRUK0065$`1`
## [ ctree - ctree rank 1/1 for CRUK0065 ]
##
## # A tibble: 3 x 10
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5 R6
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 0.99 0.99 1 1 1
## 2 2 3 TRUE FALSE 0 0 0 0 0.48 0
## 3 6 2 TRUE FALSE 0 0 0 0 0.01 0.83
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: TP53, NFE2L2, PIK3CA, SOX2
## |-2 :: MLH1, PTPRC, UBR5
## \-6 :: NOTCH1, NCOA6
##
## Information transfer
##
## GL ---> TP53
## GL ---> NFE2L2
## GL ---> PIK3CA
## GL ---> SOX2
## TP53 ---> MLH1
## TP53 ---> PTPRC
## TP53 ---> UBR5
## NFE2L2 ---> MLH1
## NFE2L2 ---> PTPRC
## NFE2L2 ---> UBR5
## PIK3CA ---> MLH1
## PIK3CA ---> PTPRC
## PIK3CA ---> UBR5
## SOX2 ---> MLH1
## SOX2 ---> PTPRC
## SOX2 ---> UBR5
## TP53 ---> NOTCH1
## TP53 ---> NCOA6
## NFE2L2 ---> NOTCH1
## NFE2L2 ---> NCOA6
## PIK3CA ---> NOTCH1
## PIK3CA ---> NCOA6
## SOX2 ---> NOTCH1
## SOX2 ---> NCOA6
##
## Tree score 1
##
##
## $phylogenies$CRUK0066
## $phylogenies$CRUK0066$`1`
## [ ctree - ctree rank 1/1 for CRUK0066 ]
##
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 7 TRUE TRUE 0.99 1 1 0.99
## 2 9 1 TRUE FALSE 0 0.91 0.01 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R4] :: TP53, NOTCH1, CDKN2A, WRN, PDGFRA, TERT, NCOA6
## \-9 :: COL5A2
##
## Information transfer
##
## GL ---> TP53
## GL ---> NOTCH1
## GL ---> CDKN2A
## GL ---> WRN
## GL ---> PDGFRA
## GL ---> TERT
## GL ---> NCOA6
## TP53 ---> COL5A2
## NOTCH1 ---> COL5A2
## CDKN2A ---> COL5A2
## WRN ---> COL5A2
## PDGFRA ---> COL5A2
## TERT ---> COL5A2
## NCOA6 ---> COL5A2
##
## Tree score 1
##
##
## $phylogenies$CRUK0067
## $phylogenies$CRUK0067$`1`
## [ ctree - ctree rank 1/1 for CRUK0067 ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 0.99 1
## 2 2 1 TRUE FALSE 0.61 0.83
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: NOTCH1, TP53, PIK3CA, SOX2, CDKN2A
## \-2 :: NFE2L2
##
## Information transfer
##
## GL ---> NOTCH1
## GL ---> TP53
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> CDKN2A
## NOTCH1 ---> NFE2L2
## TP53 ---> NFE2L2
## PIK3CA ---> NFE2L2
## SOX2 ---> NFE2L2
## CDKN2A ---> NFE2L2
##
## Tree score 1
##
##
## $phylogenies$CRUK0068
## $phylogenies$CRUK0068$`1`
## [ ctree - ctree rank 1/1 for CRUK0068 ]
##
## # A tibble: 4 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 0.99 1 1 1
## 2 3 1 TRUE FALSE 0.5 0 0 0
## 3 4 1 TRUE FALSE 0.98 0.37 0.99 0.01
## 4 9 1 TRUE FALSE 0 0 0 0.69
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53, PTEN, KMT2D, PIK3CA, SOX2
## |-4 :: SETD2
## | \-3 :: MGA
## \-9 :: TERT
##
## Information transfer
##
## GL ---> TP53
## GL ---> PTEN
## GL ---> KMT2D
## GL ---> PIK3CA
## GL ---> SOX2
## SETD2 ---> MGA
## TP53 ---> SETD2
## PTEN ---> SETD2
## KMT2D ---> SETD2
## PIK3CA ---> SETD2
## SOX2 ---> SETD2
## TP53 ---> TERT
## PTEN ---> TERT
## KMT2D ---> TERT
## PIK3CA ---> TERT
## SOX2 ---> TERT
##
## Tree score 1
##
##
## $phylogenies$CRUK0069
## $phylogenies$CRUK0069$`1`
## [ ctree - ctree rank 1/1 for CRUK0069 ]
##
## # A tibble: 2 x 9
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1 1
## 2 13 1 TRUE FALSE 0.93 0.42 0.32 0.94 0.96
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53, FAT1, PDGFRA, FGFR1
## \-13 :: KRAS
##
## Information transfer
##
## GL ---> TP53
## GL ---> FAT1
## GL ---> PDGFRA
## GL ---> FGFR1
## TP53 ---> KRAS
## FAT1 ---> KRAS
## PDGFRA ---> KRAS
## FGFR1 ---> KRAS
##
## Tree score 1
##
##
## $phylogenies$CRUK0070
## $phylogenies$CRUK0070$`1`
## [ ctree - ctree rank 1/1 for CRUK0070 ]
##
## # A tibble: 3 x 9
## cluster nMuts is.driver is.clonal R1 R2 R4 R6 R7
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1 1
## 2 2 1 TRUE FALSE 0 0 0 0.95 0.98
## 3 3 1 TRUE FALSE 0.95 0.96 0.98 0 0.01
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: DNM2, TP53, COL5A2, SOX2
## |-3 :: NFE2L2
## \-2 :: CBLB
##
## Information transfer
##
## GL ---> DNM2
## GL ---> TP53
## GL ---> COL5A2
## GL ---> SOX2
## DNM2 ---> CBLB
## TP53 ---> CBLB
## COL5A2 ---> CBLB
## SOX2 ---> CBLB
## DNM2 ---> NFE2L2
## TP53 ---> NFE2L2
## COL5A2 ---> NFE2L2
## SOX2 ---> NFE2L2
##
## Tree score 1
##
##
## $phylogenies$CRUK0071
## $phylogenies$CRUK0071$`1`
## [ ctree - ctree rank 1/1 for CRUK0071 ]
##
## # A tibble: 2 x 10
## cluster nMuts is.driver is.clonal R1 R2 R3 R5 R6 R7
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 1 0.99 1 1 1 1
## 2 4 1 TRUE FALSE 0 0.570 0 0 0 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R3, R5, R6, R7] :: CMTR2, PIK3CA, SOX2
## \-4 :: UBR5
##
## Information transfer
##
## GL ---> CMTR2
## GL ---> PIK3CA
## GL ---> SOX2
## CMTR2 ---> UBR5
## PIK3CA ---> UBR5
## SOX2 ---> UBR5
##
## Tree score 1
##
##
## $phylogenies$CRUK0072
## $phylogenies$CRUK0072$`1`
## [ ctree - ctree rank 1/1 for CRUK0072 ]
##
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 1 0.99 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R4] :: TP53, NFE2L2, PIK3CA, SOX2, EGFR, MYC
##
## Information transfer
##
## GL ---> TP53
## GL ---> NFE2L2
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> EGFR
## GL ---> MYC
##
## Tree score 1
##
##
## $phylogenies$CRUK0073
## $phylogenies$CRUK0073$`1`
## [ ctree - ctree rank 1/1 for CRUK0073 ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 8 TRUE TRUE 1 1
## 2 2 1 TRUE FALSE 0 0.93
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1] :: CDKN2A, DICER1, NFE2L2, FAT1, KMT2D, NOTCH2, FGFR1, MYC
## \-2 :: PLXNB2
##
## Information transfer
##
## GL ---> CDKN2A
## GL ---> DICER1
## GL ---> NFE2L2
## GL ---> FAT1
## GL ---> KMT2D
## GL ---> NOTCH2
## GL ---> FGFR1
## GL ---> MYC
## CDKN2A ---> PLXNB2
## DICER1 ---> PLXNB2
## NFE2L2 ---> PLXNB2
## FAT1 ---> PLXNB2
## KMT2D ---> PLXNB2
## NOTCH2 ---> PLXNB2
## FGFR1 ---> PLXNB2
## MYC ---> PLXNB2
##
## Tree score 1
##
##
## $phylogenies$CRUK0074
## $phylogenies$CRUK0074$`1`
## [ ctree - ctree rank 1/1 for CRUK0074 ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 0.99 1
## 2 3 1 TRUE FALSE 0 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1] :: TP53, NFE2L2, PIK3CA, SOX2, CCND1
## \-3 :: UBR5
##
## Information transfer
##
## GL ---> TP53
## GL ---> NFE2L2
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> CCND1
## TP53 ---> UBR5
## NFE2L2 ---> UBR5
## PIK3CA ---> UBR5
## SOX2 ---> UBR5
## CCND1 ---> UBR5
##
## Tree score 1
##
##
## $phylogenies$CRUK0075
## $phylogenies$CRUK0075$`1`
## [ ctree - ctree rank 1/1 for CRUK0075 ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 7 TRUE TRUE 1 0.99
## 2 2 1 TRUE FALSE 0.15 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: NOTCH1, RASA1, TP53, FAT1, MGA, PIK3CA, FGFR1
## \-2 :: NFE2L2
##
## Information transfer
##
## GL ---> NOTCH1
## GL ---> RASA1
## GL ---> TP53
## GL ---> FAT1
## GL ---> MGA
## GL ---> PIK3CA
## GL ---> FGFR1
## NOTCH1 ---> NFE2L2
## RASA1 ---> NFE2L2
## TP53 ---> NFE2L2
## FAT1 ---> NFE2L2
## MGA ---> NFE2L2
## PIK3CA ---> NFE2L2
## FGFR1 ---> NFE2L2
##
## Tree score 1
##
##
## $phylogenies$CRUK0076
## $phylogenies$CRUK0076$`1`
## [ ctree - ctree rank 1/3 for CRUK0076 ]
##
## # A tibble: 3 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 1 1 1 1
## 2 2 1 TRUE FALSE 0.93 0 0.28 0
## 3 3 1 TRUE FALSE 0.93 0 0.81 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R2, R4] :: SERPINB13, TP53, ARID1B, PIK3CA, SOX2, FGFR1
## \-3 :: COL5A2
## \-2 :: NCOR1
##
## Information transfer
##
## GL ---> SERPINB13
## GL ---> TP53
## GL ---> ARID1B
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> FGFR1
## COL5A2 ---> NCOR1
## SERPINB13 ---> COL5A2
## TP53 ---> COL5A2
## ARID1B ---> COL5A2
## PIK3CA ---> COL5A2
## SOX2 ---> COL5A2
## FGFR1 ---> COL5A2
##
## Tree score 0.444444444444444
##
## $phylogenies$CRUK0076$`2`
## [ ctree - ctree rank 2/3 for CRUK0076 ]
##
## # A tibble: 3 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 1 1 1 1
## 2 2 1 TRUE FALSE 0.93 0 0.28 0
## 3 3 1 TRUE FALSE 0.93 0 0.81 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R2, R4] :: SERPINB13, TP53, ARID1B, PIK3CA, SOX2, FGFR1
## |-2 :: NCOR1
## \-3 :: COL5A2
##
## Information transfer
##
## GL ---> SERPINB13
## GL ---> TP53
## GL ---> ARID1B
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> FGFR1
## SERPINB13 ---> NCOR1
## TP53 ---> NCOR1
## ARID1B ---> NCOR1
## PIK3CA ---> NCOR1
## SOX2 ---> NCOR1
## FGFR1 ---> NCOR1
## SERPINB13 ---> COL5A2
## TP53 ---> COL5A2
## ARID1B ---> COL5A2
## PIK3CA ---> COL5A2
## SOX2 ---> COL5A2
## FGFR1 ---> COL5A2
##
## Tree score 0.111111111111111
##
## $phylogenies$CRUK0076$`3`
## [ ctree - ctree rank 3/3 for CRUK0076 ]
##
## # A tibble: 3 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 1 1 1 1
## 2 2 1 TRUE FALSE 0.93 0 0.28 0
## 3 3 1 TRUE FALSE 0.93 0 0.81 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R2, R4] :: SERPINB13, TP53, ARID1B, PIK3CA, SOX2, FGFR1
## \-2 :: NCOR1
## \-3 :: COL5A2
##
## Information transfer
##
## GL ---> SERPINB13
## GL ---> TP53
## GL ---> ARID1B
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> FGFR1
## SERPINB13 ---> NCOR1
## TP53 ---> NCOR1
## ARID1B ---> NCOR1
## PIK3CA ---> NCOR1
## SOX2 ---> NCOR1
## FGFR1 ---> NCOR1
## NCOR1 ---> COL5A2
##
## Tree score 0.0833333333333333
##
##
## $phylogenies$CRUK0077
## $phylogenies$CRUK0077$`1`
## [ ctree - ctree rank 1/1 for CRUK0077 ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 1 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: TP53, LATS1, KEAP1
##
## Information transfer
##
## GL ---> TP53
## GL ---> LATS1
## GL ---> KEAP1
##
## Tree score 1
##
##
## $phylogenies$CRUK0078
## $phylogenies$CRUK0078$`1`
## [ ctree - ctree rank 1/1 for CRUK0078 ]
##
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R2, R3, R4] :: PLXNB2, PTEN, PIK3CA, SOX2, FGFR1
##
## Information transfer
##
## GL ---> PLXNB2
## GL ---> PTEN
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> FGFR1
##
## Tree score 1
##
##
## $phylogenies$CRUK0079
## $phylogenies$CRUK0079$`1`
## [ ctree - ctree rank 1/1 for CRUK0079 ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 1 0.99 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: FAT1, TP53, POLE, PIK3CA, SOX2, FGFR1
##
## Information transfer
##
## GL ---> FAT1
## GL ---> TP53
## GL ---> POLE
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> FGFR1
##
## Tree score 1
##
##
## $phylogenies$CRUK0080
## $phylogenies$CRUK0080$`1`
## [ ctree - ctree rank 1/1 for CRUK0080 ]
##
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal R3 R4 R5 R6
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1
## 2 3 1 TRUE FALSE 0 0 0.97 0.83
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R3, R4] :: TP53, WT1, EGFR, CCND1
## \-3 :: IKZF1
##
## Information transfer
##
## GL ---> TP53
## GL ---> WT1
## GL ---> EGFR
## GL ---> CCND1
## TP53 ---> IKZF1
## WT1 ---> IKZF1
## EGFR ---> IKZF1
## CCND1 ---> IKZF1
##
## Tree score 1
##
##
## $phylogenies$CRUK0081
## $phylogenies$CRUK0081$`1`
## [ ctree - ctree rank 1/1 for CRUK0081 ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R5
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 1 0.99
## 2 3 1 TRUE FALSE 0.93 0.01
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: NOTCH1, TP53, CDKN2A, FAT1, FANCC
## \-3 :: CYLD
##
## Information transfer
##
## GL ---> NOTCH1
## GL ---> TP53
## GL ---> CDKN2A
## GL ---> FAT1
## GL ---> FANCC
## NOTCH1 ---> CYLD
## TP53 ---> CYLD
## CDKN2A ---> CYLD
## FAT1 ---> CYLD
## FANCC ---> CYLD
##
## Tree score 1
##
##
## $phylogenies$CRUK0082
## $phylogenies$CRUK0082$`1`
## [ ctree - ctree rank 1/1 for CRUK0082 ]
##
## # A tibble: 1 x 9
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 8 TRUE TRUE 1 1 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4, R5] :: TP53, WT1, PTEN, COL5A2, KMT2D, PIK3CA, SOX2, FGFR1
##
## Information transfer
##
## GL ---> TP53
## GL ---> WT1
## GL ---> PTEN
## GL ---> COL5A2
## GL ---> KMT2D
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> FGFR1
##
## Tree score 1
##
##
## $phylogenies$CRUK0083
## $phylogenies$CRUK0083$`1`
## [ ctree - ctree rank 1/1 for CRUK0083 ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 7 TRUE TRUE 1 1 1 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: TP53, FBXW7, RASA1, PIK3CA, SOX2, FGFR1, MYC
##
## Information transfer
##
## GL ---> TP53
## GL ---> FBXW7
## GL ---> RASA1
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> FGFR1
## GL ---> MYC
##
## Tree score 1
##
##
## $phylogenies$CRUK0084
## $phylogenies$CRUK0084$`1`
## [ ctree - ctree rank 1/1 for CRUK0084 ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 1 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: CREBBP
##
## Information transfer
##
## GL ---> CREBBP
##
## Tree score 1
##
##
## $phylogenies$CRUK0085
## $phylogenies$CRUK0085$`1`
## [ ctree - ctree rank 1/1 for CRUK0085 ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: CHEK2, CREBBP, LATS1, FANCM
##
## Information transfer
##
## GL ---> CHEK2
## GL ---> CREBBP
## GL ---> LATS1
## GL ---> FANCM
##
## Tree score 1
##
##
## $phylogenies$CRUK0086
## $phylogenies$CRUK0086$`1`
## [ ctree - ctree rank 1/1 for CRUK0086 ]
##
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R4] :: TP53, ARID2, FAT1
##
## Information transfer
##
## GL ---> TP53
## GL ---> ARID2
## GL ---> FAT1
##
## Tree score 1
##
##
## $phylogenies$CRUK0087
## $phylogenies$CRUK0087$`1`
## [ ctree - ctree rank 1/1 for CRUK0087 ]
##
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3] :: NFE2L2, TP53, ASXL1, PIK3CA
##
## Information transfer
##
## GL ---> NFE2L2
## GL ---> TP53
## GL ---> ASXL1
## GL ---> PIK3CA
##
## Tree score 1
##
##
## $phylogenies$CRUK0088
## $phylogenies$CRUK0088$`1`
## [ ctree - ctree rank 1/1 for CRUK0088 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: CUX1, TP53
##
## Information transfer
##
## GL ---> CUX1
## GL ---> TP53
##
## Tree score 1
##
##
## $phylogenies$CRUK0089
## $phylogenies$CRUK0089$`1`
## [ ctree - ctree rank 1/1 for CRUK0089 ]
##
## # A tibble: 1 x 5
## cluster nMuts is.driver is.clonal R2
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 3 TRUE TRUE 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R2] :: PIK3CA, SMAD4, KEAP1
##
## Information transfer
##
## GL ---> PIK3CA
## GL ---> SMAD4
## GL ---> KEAP1
##
## Tree score 1
##
##
## $phylogenies$CRUK0090
## $phylogenies$CRUK0090$`1`
## [ ctree - ctree rank 1/1 for CRUK0090 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: CDKN2A, NCOA6, CUX1, COL2A1, NRAS
##
## Information transfer
##
## GL ---> CDKN2A
## GL ---> NCOA6
## GL ---> CUX1
## GL ---> COL2A1
## GL ---> NRAS
##
## Tree score 1
##
##
## $phylogenies$CRUK0091
## $phylogenies$CRUK0091$`1`
## [ ctree - ctree rank 1/1 for CRUK0091 ]
##
## # A tibble: 1 x 5
## cluster nMuts is.driver is.clonal R2
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 3 TRUE TRUE 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R2] :: TP53, SMARCA4, CDKN2A
##
## Information transfer
##
## GL ---> TP53
## GL ---> SMARCA4
## GL ---> CDKN2A
##
## Tree score 1
##
##
## $phylogenies$CRUK0092
## $phylogenies$CRUK0092$`1`
## [ ctree - ctree rank 1/1 for CRUK0092 ]
##
## # A tibble: 1 x 5
## cluster nMuts is.driver is.clonal R1
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 5 TRUE TRUE 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1] :: TP53, SMAD4, RASA1, CBLB, PIK3CA
##
## Information transfer
##
## GL ---> TP53
## GL ---> SMAD4
## GL ---> RASA1
## GL ---> CBLB
## GL ---> PIK3CA
##
## Tree score 1
##
##
## $phylogenies$CRUK0093
## $phylogenies$CRUK0093$`1`
## [ ctree - ctree rank 1/1 for CRUK0093 ]
##
## # A tibble: 1 x 5
## cluster nMuts is.driver is.clonal R1
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 7 TRUE TRUE 0.96
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1] :: DICER1, CDKN2A, COL2A1, GATA3, CIC, COL5A2, TP53
##
## Information transfer
##
## GL ---> DICER1
## GL ---> CDKN2A
## GL ---> COL2A1
## GL ---> GATA3
## GL ---> CIC
## GL ---> COL5A2
## GL ---> TP53
##
## Tree score 1
##
##
## $phylogenies$CRUK0094
## $phylogenies$CRUK0094$`1`
## [ ctree - ctree rank 1/1 for CRUK0094 ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.98 0.98 0.97 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: SMARCA4, TERT
##
## Information transfer
##
## GL ---> SMARCA4
## GL ---> TERT
##
## Tree score 1
##
##
## $phylogenies$CRUK0095
## $phylogenies$CRUK0095$`1`
## [ ctree - ctree rank 1/1 for CRUK0095 ]
##
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.99 0.99 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3] :: TP53, NF1, RASA1
##
## Information transfer
##
## GL ---> TP53
## GL ---> NF1
## GL ---> RASA1
##
## Tree score 1
##
##
## $phylogenies$CRUK0096
## $phylogenies$CRUK0096$`1`
## [ ctree - ctree rank 1/1 for CRUK0096 ]
##
## # A tibble: 1 x 11
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5 R6
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 1 1 1 1 1 1
## # … with 1 more variable: R7 <dbl>
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4, R5, R6, R7] :: KRAS, SGK223, MAP3K1
##
## Information transfer
##
## GL ---> KRAS
## GL ---> SGK223
## GL ---> MAP3K1
##
## Tree score 1
##
##
## $phylogenies$CRUK0097
## $phylogenies$CRUK0097$`1`
## [ ctree - ctree rank 1/1 for CRUK0097 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.995 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: TP53, PTEN
##
## Information transfer
##
## GL ---> TP53
## GL ---> PTEN
##
## Tree score 1
##
##
## $phylogenies$CRUK0098
## $phylogenies$CRUK0098$`1`
## [ ctree - ctree rank 1/1 for CRUK0098 ]
##
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 1 1 1
## 2 3 1 TRUE FALSE 0.96 0.91 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R3] :: TP53, PTEN
## \-3 :: UBR5
##
## Information transfer
##
## GL ---> TP53
## GL ---> PTEN
## TP53 ---> UBR5
## PTEN ---> UBR5
##
## Tree score 1
##
##
## $phylogenies$CRUK0099
## $phylogenies$CRUK0099$`1`
## [ ctree - ctree rank 1/1 for CRUK0099 ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R3 R6 R7
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.95 0.97 0.91 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R3, R6, R7] :: STK11, KEAP1, TP53
##
## Information transfer
##
## GL ---> STK11
## GL ---> KEAP1
## GL ---> TP53
##
## Tree score 1
##
##
## $phylogenies$CRUK0100
## $phylogenies$CRUK0100$`1`
## [ ctree - ctree rank 1/1 for CRUK0100 ]
##
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3] :: TP53, PHOX2B, COL5A2, STK11, SPEN, CDKN2A
##
## Information transfer
##
## GL ---> TP53
## GL ---> PHOX2B
## GL ---> COL5A2
## GL ---> STK11
## GL ---> SPEN
## GL ---> CDKN2A
##
## Tree score 1
##
##
##
## $fit
## $fit$fit_table
## # A tibble: 99 x 9
## patientID hasTrees numTrees maxScore minScore combInfTransf Solution
## <chr> <lgl> <int> <dbl> <dbl> <int> <int>
## 1 CRUK0001 TRUE 3 0.111 0.111 3 1
## 2 CRUK0002 TRUE 2 0.75 0.0833 2 1
## 3 CRUK0003 TRUE 1 1 1 1 1
## 4 CRUK0004 TRUE 1 1 1 1 1
## 5 CRUK0005 TRUE 1 1 1 1 1
## 6 CRUK0006 TRUE 2 0.667 0.167 2 1
## 7 CRUK0007 TRUE 1 1 1 1 1
## 8 CRUK0008 TRUE 1 1 1 1 1
## 9 CRUK0009 TRUE 1 1 1 1 1
## 10 CRUK0010 TRUE 1 1 1 1 1
## # … with 89 more rows, and 2 more variables: converged <lgl>,
## # penalty <dbl>
##
## $fit$penalty
## # A tibble: 262 x 4
## from to count penalty
## <chr> <chr> <int> <dbl>
## 1 ARHGAP35 TERT 2 0.08
## 2 ARID1B ASXL1 1 0.333
## 3 ARID1B COL5A2 1 0.0455
## 4 ARID1B KRAS 1 0.0222
## 5 ARID2 KRAS 2 0.0444
## 6 ATM CCND1 1 0.125
## 7 ATM MGA 1 0.1
## 8 ATM NCOR1 1 0.125
## 9 BAP1 PIK3CA 1 0.0476
## 10 BAP1 RB1 1 0.2
## # … with 252 more rows
##
## $fit$phylogenies
## $fit$phylogenies$CRUK0001
## [ ctree - ctree rank 1/3 for CRUK0001 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 4 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 3 4 TRUE TRUE 0.99 0.99 1
## 2 1 1 TRUE FALSE 0.86 0 0
## 3 2 1 TRUE FALSE 0.19 0 0.95
## 4 5 1 TRUE FALSE 0.82 0 0.71
##
## Tree shape (drivers annotated)
##
## \-GL
## \-3 [R2] :: TP53, MGA, WRN, EGFR
## |-1 :: NF1
## | \-5 :: PASK
## \-2 :: ARHGAP35
##
## Information transfer
##
## GL ---> EGFR
## GL ---> WRN
## GL ---> MGA
## EGFR ---> TP53
## WRN ---> TP53
## TP53 ---> NF1
## MGA ---> NF1
## TP53 ---> ARHGAP35
## MGA ---> ARHGAP35
## NF1 ---> PASK
##
## Tree score 0.111111111111111
##
## $fit$phylogenies$CRUK0002
## [ ctree - ctree rank 1/2 for CRUK0002 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 4 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE FALSE 0 0.92 0
## 2 2 2 TRUE TRUE 0.99 0.98 0.99
## 3 5 1 TRUE FALSE 0.78 0 0
## 4 6 1 TRUE FALSE 0.96 0.03 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-2 :: MET, TERT
## |-6 :: EP300
## | \-5 :: NF1
## \-1 :: RB1, IKZF1, KRAS
##
## Information transfer
##
## GL ---> MET
## MET ---> TERT
## TERT ---> EP300
## TERT ---> RB1
## TERT ---> IKZF1
## TERT ---> KRAS
## EP300 ---> NF1
##
## Tree score 0.75
##
## $fit$phylogenies$CRUK0003
## [ ctree - ctree rank 1/1 for CRUK0003 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 9
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R6
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.98 0.97 0.87 0.97 0.99
## 2 4 1 TRUE FALSE 0 0 0.49 0 0.01
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R4] :: PIK3CA, EGFR, CDKN2A
## \-4 :: CTNNB1
##
## Information transfer
##
## GL ---> PIK3CA
## GL ---> EGFR
## GL ---> CDKN2A
## PIK3CA ---> CTNNB1
## EGFR ---> CTNNB1
## CDKN2A ---> CTNNB1
##
## Tree score 1
##
## $fit$phylogenies$CRUK0004
## [ ctree - ctree rank 1/1 for CRUK0004 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 2 TRUE FALSE 0 0 0.95 0.01
## 2 2 2 TRUE TRUE 0.99 0.985 0.99 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-2 [R1, R2] :: TP53, EGFR
## \-1 :: SMAD4, NOTCH1
##
## Information transfer
##
## GL ---> EGFR
## EGFR ---> TP53
## TP53 ---> SMAD4
## TP53 ---> NOTCH1
##
## Tree score 1
##
## $fit$phylogenies$CRUK0005
## [ ctree - ctree rank 1/1 for CRUK0005 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 2 5 TRUE TRUE 1 1 0.97 1
## 2 1 1 TRUE FALSE 0 0 0.8 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-2 [R1, R2, R4] :: CMTR2, TP53, BRAF, PASK, TERT
## \-1 :: NRAS
##
## Information transfer
##
## GL ---> BRAF
## GL ---> TP53
## GL ---> CMTR2
## GL ---> PASK
## BRAF ---> TERT
## TP53 ---> TERT
## CMTR2 ---> NRAS
## PASK ---> NRAS
## TERT ---> NRAS
##
## Tree score 1
##
## $fit$phylogenies$CRUK0006
## [ ctree - ctree rank 1/2 for CRUK0006 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 3 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1
## 2 2 1 TRUE FALSE 0 0.93
## 3 7 1 TRUE FALSE 0.99 0.06
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: PLXNB2, TP53, KEAP1, TERT
## |-7 :: FANCC
## \-2 :: MAP3K1
##
## Information transfer
##
## GL ---> TP53
## GL ---> KEAP1
## TP53 ---> PLXNB2
## TP53 ---> TERT
## PLXNB2 ---> MAP3K1
## KEAP1 ---> MAP3K1
## TERT ---> MAP3K1
## PLXNB2 ---> FANCC
## KEAP1 ---> FANCC
## TERT ---> FANCC
##
## Tree score 0.666666666666667
##
## $fit$phylogenies$CRUK0007
## [ ctree - ctree rank 1/1 for CRUK0007 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.98 0.93
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: PIK3CA, EGFR, SGK223
##
## Information transfer
##
## GL ---> PIK3CA
## GL ---> EGFR
## GL ---> SGK223
##
## Tree score 1
##
## $fit$phylogenies$CRUK0008
## [ ctree - ctree rank 1/1 for CRUK0008 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 2 5 TRUE TRUE 0.99 1
## 2 3 1 TRUE FALSE 0.86 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-2 [R2] :: KEAP1, STK11, PRDM1, U2AF1, MYC
## \-3 :: ARID2
##
## Information transfer
##
## GL ---> KEAP1
## GL ---> STK11
## GL ---> PRDM1
## GL ---> U2AF1
## GL ---> MYC
## KEAP1 ---> ARID2
## STK11 ---> ARID2
## PRDM1 ---> ARID2
## U2AF1 ---> ARID2
## MYC ---> ARID2
##
## Tree score 1
##
## $fit$phylogenies$CRUK0009
## [ ctree - ctree rank 1/1 for CRUK0009 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 0.99 0.99 0.98 0.99
## 2 2 1 TRUE FALSE 0 0.93 0 0.96
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R3] :: BRAF, TP53, ARHGAP35, KMT2C, NFE2L2, MET
## \-2 :: TERT
##
## Information transfer
##
## GL ---> TP53
## GL ---> BRAF
## GL ---> KMT2C
## GL ---> MET
## TP53 ---> ARHGAP35
## TP53 ---> NFE2L2
## BRAF ---> TERT
## ARHGAP35 ---> TERT
## KMT2C ---> TERT
## NFE2L2 ---> TERT
## MET ---> TERT
##
## Tree score 1
##
## $fit$phylogenies$CRUK0010
## [ ctree - ctree rank 1/1 for CRUK0010 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.95 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: SETD2, EGFR, TERT
##
## Information transfer
##
## GL ---> SETD2
## GL ---> EGFR
## GL ---> TERT
##
## Tree score 1
##
## $fit$phylogenies$CRUK0011
## [ ctree - ctree rank 1/1 for CRUK0011 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.97 1
## 2 3 1 TRUE FALSE 0.95 0 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R2, R3] :: KRAS
## \-3 :: FLT4
##
## Information transfer
##
## GL ---> KRAS
## KRAS ---> FLT4
##
## Tree score 1
##
## $fit$phylogenies$CRUK0012
## [ ctree - ctree rank 1/1 for CRUK0012 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.98 0.95
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: EGFR
##
## Information transfer
##
## GL ---> EGFR
##
## Tree score 1
##
## $fit$phylogenies$CRUK0013
## [ ctree - ctree rank 1/4 for CRUK0013 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 4 x 9
## cluster nMuts is.driver is.clonal LN1 LN2 R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.99 0.99 0.99 0.99
## 2 2 1 TRUE FALSE 0 0 0 0.75 0
## 3 3 1 TRUE FALSE 0.97 0.96 0.01 0.580 0.94
## 4 4 1 TRUE FALSE 0 0 0.97 0.37 0.01
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: STK11
## |-3 :: KRAS
## |-4 :: EGFR
## \-2 :: NOTCH1
##
## Information transfer
##
## GL ---> STK11
## STK11 ---> NOTCH1
## STK11 ---> KRAS
## STK11 ---> EGFR
##
## Tree score 0.3
##
## $fit$phylogenies$CRUK0014
## [ ctree - ctree rank 1/1 for CRUK0014 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.96 0.96
## 2 2 1 TRUE FALSE 0.35 0.01
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53, KRAS
## \-2 :: RNF43
##
## Information transfer
##
## GL ---> KRAS
## GL ---> TP53
## KRAS ---> TP53
## TP53 ---> KRAS
## KRAS ---> RNF43
## TP53 ---> RNF43
##
## Tree score 1
##
## $fit$phylogenies$CRUK0015
## [ ctree - ctree rank 1/1 for CRUK0015 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 3 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.99 0.99
## 2 2 1 TRUE FALSE 0.94 0.01
## 3 3 1 TRUE FALSE 0.01 0.65
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: BAP1, EGFR
## |-2 :: TP53
## \-3 :: RB1
##
## Information transfer
##
## GL ---> BAP1
## GL ---> EGFR
## BAP1 ---> TP53
## EGFR ---> TP53
## BAP1 ---> RB1
## EGFR ---> RB1
##
## Tree score 1
##
## $fit$phylogenies$CRUK0016
## [ ctree - ctree rank 1/13 for CRUK0016 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 5 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 0.99 0.99
## 2 16 2 TRUE FALSE 0.97 0
## 3 10 1 TRUE FALSE 0.34 0.3
## 4 2 1 TRUE FALSE 0.53 0
## 5 6 1 TRUE FALSE 0.31 0.53
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53, FAT1, SPEN, CBLB, TERT, CDKN2A
## |-16 :: LATS1, ARID1B
## | \-2 :: ASXL1
## |-10 :: DNM2
## \-6 :: PTPRC
##
## Information transfer
##
## GL ---> CDKN2A
## GL ---> SPEN
## CDKN2A ---> TP53
## TP53 ---> FAT1
## TP53 ---> CBLB
## TP53 ---> TERT
## FAT1 ---> LATS1
## SPEN ---> LATS1
## CBLB ---> LATS1
## TERT ---> LATS1
## FAT1 ---> ARID1B
## SPEN ---> ARID1B
## CBLB ---> ARID1B
## TERT ---> ARID1B
## FAT1 ---> DNM2
## SPEN ---> DNM2
## CBLB ---> DNM2
## TERT ---> DNM2
## FAT1 ---> PTPRC
## SPEN ---> PTPRC
## CBLB ---> PTPRC
## TERT ---> PTPRC
## LATS1 ---> ASXL1
## ARID1B ---> ASXL1
##
## Tree score 0.03125
##
## $fit$phylogenies$CRUK0017
## [ ctree - ctree rank 1/1 for CRUK0017 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 1 1 1 1
## 2 3 1 TRUE FALSE 0 0.94 0.95 0.59
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1] :: TP53, ARID1B, ARID2, KEAP1, MYC
## \-3 :: KRAS
##
## Information transfer
##
## GL ---> KEAP1
## GL ---> MYC
## GL ---> TP53
## KEAP1 ---> ARID2
## MYC ---> ARID2
## TP53 ---> ARID1B
## ARID1B ---> KRAS
## ARID2 ---> KRAS
##
## Tree score 1
##
## $fit$phylogenies$CRUK0018
## [ ctree - ctree rank 1/1 for CRUK0018 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: CMTR2, KRAS, MGA, COL5A2
##
## Information transfer
##
## GL ---> KRAS
## GL ---> CMTR2
## GL ---> COL5A2
## KRAS ---> MGA
##
## Tree score 1
##
## $fit$phylogenies$CRUK0019
## [ ctree - ctree rank 1/1 for CRUK0019 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.97 0.96
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: EGFR
##
## Information transfer
##
## GL ---> EGFR
##
## Tree score 1
##
## $fit$phylogenies$CRUK0020
## [ ctree - ctree rank 1/2 for CRUK0020 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 4 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 7 TRUE TRUE 1 1
## 2 2 1 TRUE FALSE 0.87 0
## 3 3 1 TRUE FALSE 0.9 0.08
## 4 4 1 TRUE FALSE 0 0.85
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: KEAP1, TP53, MGA, ARID2, COL2A1, PRF1, KRAS
## |-3 :: BAP1
## | \-2 :: PIK3CA
## \-4 :: NCOR1
##
## Information transfer
##
## GL ---> KEAP1
## GL ---> COL2A1
## GL ---> PRF1
## GL ---> KRAS
## GL ---> TP53
## ARID2 ---> KRAS
## KEAP1 ---> ARID2
## KEAP1 ---> KRAS
## KRAS ---> TP53
## KRAS ---> MGA
## TP53 ---> KRAS
## MGA ---> BAP1
## COL2A1 ---> BAP1
## PRF1 ---> BAP1
## KRAS ---> BAP1
## TP53 ---> BAP1
## MGA ---> NCOR1
## COL2A1 ---> NCOR1
## PRF1 ---> NCOR1
## KRAS ---> NCOR1
## TP53 ---> NCOR1
## BAP1 ---> PIK3CA
##
## Tree score 0.666666666666667
##
## $fit$phylogenies$CRUK0021
## [ ctree - ctree rank 1/1 for CRUK0021 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: EGFR, TP53, CHEK2, CDKN2A
##
## Information transfer
##
## GL ---> CDKN2A
## GL ---> EGFR
## GL ---> CHEK2
## CDKN2A ---> TP53
## EGFR ---> TP53
##
## Tree score 1
##
## $fit$phylogenies$CRUK0022
## [ ctree - ctree rank 1/1 for CRUK0022 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.99 0.99
## 2 2 1 TRUE FALSE 0.85 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R2] :: TP53, EGFR
## \-2 :: CIC
##
## Information transfer
##
## GL ---> EGFR
## EGFR ---> TP53
## TP53 ---> CIC
##
## Tree score 1
##
## $fit$phylogenies$CRUK0023
## [ ctree - ctree rank 1/1 for CRUK0023 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 3 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.99 0.98 0.99 0.95
## 2 4 2 TRUE FALSE 0.01 0.945 0 0
## 3 2 1 TRUE FALSE 0.81 0 0 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R3, R4] :: WRN, KRAS, CDKN2A
## |-2 :: TP53
## \-4 :: PTPRC, KMT2D
##
## Information transfer
##
## GL ---> WRN
## GL ---> KRAS
## GL ---> CDKN2A
## WRN ---> PTPRC
## KRAS ---> PTPRC
## CDKN2A ---> PTPRC
## WRN ---> KMT2D
## KRAS ---> KMT2D
## CDKN2A ---> KMT2D
## WRN ---> TP53
## KRAS ---> TP53
## CDKN2A ---> TP53
##
## Tree score 1
##
## $fit$phylogenies$CRUK0024
## [ ctree - ctree rank 1/1 for CRUK0024 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 3 x 8
## cluster nMuts is.driver is.clonal R1 R3 R4 R6
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1
## 2 3 1 TRUE FALSE 0.88 0.97 0.95 0
## 3 4 1 TRUE FALSE 0.83 0 0 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R6] :: TP53, STK11, POLE, EGFR
## \-3 :: ATM
## \-4 :: NCOR1
##
## Information transfer
##
## GL ---> STK11
## GL ---> POLE
## EGFR ---> TP53
## STK11 ---> EGFR
## TP53 ---> ATM
## POLE ---> ATM
## ATM ---> NCOR1
##
## Tree score 1
##
## $fit$phylogenies$CRUK0025
## [ ctree - ctree rank 1/1 for CRUK0025 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3] :: KRAS, TP53, MGA
##
## Information transfer
##
## GL ---> KRAS
## GL ---> TP53
## KRAS ---> TP53
## KRAS ---> MGA
## TP53 ---> KRAS
##
## Tree score 1
##
## $fit$phylogenies$CRUK0026
## [ ctree - ctree rank 1/1 for CRUK0026 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 0.98 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: TP53, EGFR, RB1, SERPINB13
##
## Information transfer
##
## GL ---> EGFR
## GL ---> SERPINB13
## EGFR ---> TP53
## EGFR ---> RB1
##
## Tree score 1
##
## $fit$phylogenies$CRUK0027
## [ ctree - ctree rank 1/1 for CRUK0027 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.96 1
## 2 2 1 TRUE FALSE 0 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1] :: KRAS, TP53
## \-2 :: PLXNB2
##
## Information transfer
##
## GL ---> KRAS
## GL ---> TP53
## KRAS ---> TP53
## TP53 ---> KRAS
## KRAS ---> PLXNB2
## TP53 ---> PLXNB2
##
## Tree score 1
##
## $fit$phylogenies$CRUK0028
## [ ctree - ctree rank 1/1 for CRUK0028 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.975 0.95
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: APC, EGFR
##
## Information transfer
##
## GL ---> APC
## GL ---> EGFR
##
## Tree score 1
##
## $fit$phylogenies$CRUK0029
## [ ctree - ctree rank 1/1 for CRUK0029 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 10
## cluster nMuts is.driver is.clonal R2 R4 R5 R6 R7 R8
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 0.99 0.98 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R2, R4, R5, R6, R7, R8] :: TP53, NRAS, MGA, CCND1
##
## Information transfer
##
## GL ---> TP53
## GL ---> MGA
## GL ---> CCND1
## TP53 ---> NRAS
##
## Tree score 1
##
## $fit$phylogenies$CRUK0030
## [ ctree - ctree rank 1/1 for CRUK0030 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 1 0.98 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3] :: KRAS, TSC2, U2AF1, TP53, FBXW7, NF1
##
## Information transfer
##
## GL ---> TSC2
## GL ---> U2AF1
## GL ---> FBXW7
## GL ---> KRAS
## GL ---> TP53
## KRAS ---> TP53
## TP53 ---> KRAS
## TP53 ---> NF1
##
## Tree score 1
##
## $fit$phylogenies$CRUK0031
## [ ctree - ctree rank 1/1 for CRUK0031 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1
## 2 6 1 TRUE FALSE 0.88 0.05 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R3] :: KEAP1, CDKN2A, PRF1, FGFR1
## \-6 :: NF1
##
## Information transfer
##
## GL ---> KEAP1
## GL ---> CDKN2A
## GL ---> PRF1
## GL ---> FGFR1
## KEAP1 ---> NF1
## CDKN2A ---> NF1
## PRF1 ---> NF1
## FGFR1 ---> NF1
##
## Tree score 1
##
## $fit$phylogenies$CRUK0032
## [ ctree - ctree rank 1/1 for CRUK0032 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 3 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1
## 2 4 1 TRUE FALSE 0 0.97 0 0.98
## 3 6 1 TRUE FALSE 0 0 0 0.3
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R3] :: ATM, RAD21, U2AF1, RNF43
## \-4 :: CCND1
## \-6 :: ARID1B
##
## Information transfer
##
## GL ---> ATM
## GL ---> RAD21
## GL ---> U2AF1
## GL ---> RNF43
## ATM ---> CCND1
## RAD21 ---> CCND1
## U2AF1 ---> CCND1
## RNF43 ---> CCND1
## CCND1 ---> ARID1B
##
## Tree score 1
##
## $fit$phylogenies$CRUK0033
## [ ctree - ctree rank 1/1 for CRUK0033 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.99 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: KEAP1, CTNNB1
##
## Information transfer
##
## GL ---> KEAP1
## GL ---> CTNNB1
##
## Tree score 1
##
## $fit$phylogenies$CRUK0034
## [ ctree - ctree rank 1/1 for CRUK0034 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 1 1 1
## 2 4 1 TRUE FALSE 0 0.5 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R3] :: ATM, KRAS, PLXNB2
## \-4 :: MGA
##
## Information transfer
##
## GL ---> KRAS
## GL ---> ATM
## KRAS ---> PLXNB2
## ATM ---> MGA
## PLXNB2 ---> MGA
##
## Tree score 1
##
## $fit$phylogenies$CRUK0035
## [ ctree - ctree rank 1/1 for CRUK0035 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal LN1 R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.98 0.98 0.99 0.99
## 2 4 1 TRUE FALSE 0 0.8 0 0.01
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [LN1, R2] :: TP53, FAS
## \-4 :: FLT4
##
## Information transfer
##
## GL ---> TP53
## TP53 ---> FAS
## FAS ---> FLT4
##
## Tree score 1
##
## $fit$phylogenies$CRUK0036
## [ ctree - ctree rank 1/1 for CRUK0036 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 0.99 0.98 0.97 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: KRAS, PIK3CA, KEAP1, ARHGAP35, TERT
##
## Information transfer
##
## GL ---> ARHGAP35
## GL ---> KEAP1
## GL ---> PIK3CA
## ARHGAP35 ---> TERT
## KEAP1 ---> KRAS
## PIK3CA ---> TERT
## TERT ---> KRAS
##
## Tree score 1
##
## $fit$phylogenies$CRUK0037
## [ ctree - ctree rank 1/1 for CRUK0037 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 9
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.99 1 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4, R5] :: NCOA6, CREBBP, KRAS
##
## Information transfer
##
## GL ---> NCOA6
## GL ---> CREBBP
## GL ---> KRAS
##
## Tree score 1
##
## $fit$phylogenies$CRUK0038
## [ ctree - ctree rank 1/1 for CRUK0038 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.99
## 2 3 1 TRUE FALSE 0 0.38
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1] :: KRAS
## \-3 :: KMT2D
##
## Information transfer
##
## GL ---> KRAS
## KRAS ---> KMT2D
##
## Tree score 1
##
## $fit$phylogenies$CRUK0039
## [ ctree - ctree rank 1/1 for CRUK0039 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3] :: KRAS, CMTR2, NF1, PHOX2B
##
## Information transfer
##
## GL ---> KRAS
## GL ---> CMTR2
## GL ---> NF1
## GL ---> PHOX2B
##
## Tree score 1
##
## $fit$phylogenies$CRUK0040
## [ ctree - ctree rank 1/1 for CRUK0040 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 0.99 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: NCOR1, RAD21, KRAS, GATA3
##
## Information transfer
##
## GL ---> KRAS
## GL ---> RAD21
## GL ---> GATA3
## KRAS ---> NCOR1
##
## Tree score 1
##
## $fit$phylogenies$CRUK0041
## [ ctree - ctree rank 1/1 for CRUK0041 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.98 0.99 0.99 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: BRAF, TERT, EGFR
##
## Information transfer
##
## GL ---> BRAF
## GL ---> EGFR
## BRAF ---> TERT
##
## Tree score 1
##
## $fit$phylogenies$CRUK0042
## [ ctree - ctree rank 1/1 for CRUK0042 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 5
## cluster nMuts is.driver is.clonal R1
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 1 TRUE TRUE 0.91
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1] :: KRAS
##
## Information transfer
##
## GL ---> KRAS
##
## Tree score 1
##
## $fit$phylogenies$CRUK0043
## [ ctree - ctree rank 1/1 for CRUK0043 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: MET
##
## Information transfer
##
## GL ---> MET
##
## Tree score 1
##
## $fit$phylogenies$CRUK0044
## [ ctree - ctree rank 1/1 for CRUK0044 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: KRAS
##
## Information transfer
##
## GL ---> KRAS
##
## Tree score 1
##
## $fit$phylogenies$CRUK0045
## [ ctree - ctree rank 1/1 for CRUK0045 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.98 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R3] :: BAP1
##
## Information transfer
##
## GL ---> BAP1
##
## Tree score 1
##
## $fit$phylogenies$CRUK0046
## [ ctree - ctree rank 1/1 for CRUK0046 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 1 0.98 0.995 0.96
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: KEAP1, APC
##
## Information transfer
##
## GL ---> KEAP1
## GL ---> APC
##
## Tree score 1
##
## $fit$phylogenies$CRUK0047
## [ ctree - ctree rank 1/1 for CRUK0047 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 0.99 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: STK11, APC, KRAS, MYC
##
## Information transfer
##
## GL ---> MYC
## GL ---> STK11
## GL ---> APC
## MYC ---> KRAS
## STK11 ---> KRAS
##
## Tree score 1
##
## $fit$phylogenies$CRUK0048
## [ ctree - ctree rank 1/1 for CRUK0048 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 7 TRUE TRUE 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3] :: APC, PRDM1, ARHGAP35, TP53, BRAF, EGFR, MYC
##
## Information transfer
##
## GL ---> EGFR
## GL ---> APC
## GL ---> PRDM1
## GL ---> BRAF
## GL ---> MYC
## EGFR ---> TP53
## EGFR ---> ARHGAP35
## TP53 ---> ARHGAP35
##
## Tree score 1
##
## $fit$phylogenies$CRUK0049
## [ ctree - ctree rank 1/1 for CRUK0049 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: RB1, TP53, COL2A1, EGFR, KRAS
##
## Information transfer
##
## GL ---> EGFR
## GL ---> COL2A1
## GL ---> KRAS
## GL ---> TP53
## EGFR ---> TP53
## EGFR ---> RB1
## KRAS ---> TP53
## TP53 ---> KRAS
##
## Tree score 1
##
## $fit$phylogenies$CRUK0050
## [ ctree - ctree rank 1/1 for CRUK0050 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 9
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.99 0.99 0.99 1 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4, R5] :: KRAS, STK11, MYC
##
## Information transfer
##
## GL ---> MYC
## GL ---> STK11
## MYC ---> KRAS
## STK11 ---> KRAS
##
## Tree score 1
##
## $fit$phylogenies$CRUK0051
## [ ctree - ctree rank 1/1 for CRUK0051 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1
## 2 3 1 TRUE FALSE 0.97 0 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R3, R4] :: KRAS, FBXW7, TP53, EGFR
## \-3 :: EP300
##
## Information transfer
##
## GL ---> EGFR
## GL ---> FBXW7
## GL ---> KRAS
## GL ---> TP53
## EGFR ---> TP53
## KRAS ---> TP53
## TP53 ---> KRAS
## FBXW7 ---> EP300
## KRAS ---> EP300
## TP53 ---> EP300
##
## Tree score 1
##
## $fit$phylogenies$CRUK0052
## [ ctree - ctree rank 1/1 for CRUK0052 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R1 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 8 TRUE TRUE 1 1 1
## 2 2 1 TRUE FALSE 0 0 0.86
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R3] :: KMT2D, KRAS, NOTCH2, MGA, KEAP1, TP53, NF1, SGK223
## \-2 :: UBR5
##
## Information transfer
##
## GL ---> KEAP1
## GL ---> NOTCH2
## GL ---> SGK223
## GL ---> KRAS
## GL ---> TP53
## KEAP1 ---> KRAS
## KEAP1 ---> NF1
## KRAS ---> MGA
## KRAS ---> TP53
## KRAS ---> KMT2D
## MGA ---> NF1
## TP53 ---> KRAS
## TP53 ---> NF1
## KMT2D ---> UBR5
## NOTCH2 ---> UBR5
## NF1 ---> UBR5
## SGK223 ---> UBR5
## KRAS ---> UBR5
## TP53 ---> UBR5
##
## Tree score 1
##
## $fit$phylogenies$CRUK0054
## [ ctree - ctree rank 1/1 for CRUK0054 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: EGFR
##
## Information transfer
##
## GL ---> EGFR
##
## Tree score 1
##
## $fit$phylogenies$CRUK0055
## [ ctree - ctree rank 1/1 for CRUK0055 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 5
## cluster nMuts is.driver is.clonal R2
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 2 TRUE TRUE 1
## 2 2 1 TRUE FALSE 0.32
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: FANCM, UBR5
## \-2 :: FAT1
##
## Information transfer
##
## GL ---> FANCM
## GL ---> UBR5
## FANCM ---> FAT1
## UBR5 ---> FAT1
##
## Tree score 1
##
## $fit$phylogenies$CRUK0056
## [ ctree - ctree rank 1/1 for CRUK0056 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 1 1 1
## 2 3 1 TRUE FALSE 0 0.12 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1] :: RASA1, CREBBP
## \-3 :: TP53
##
## Information transfer
##
## GL ---> RASA1
## GL ---> CREBBP
## RASA1 ---> TP53
## CREBBP ---> TP53
##
## Tree score 1
##
## $fit$phylogenies$CRUK0057
## [ ctree - ctree rank 1/1 for CRUK0057 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: KRAS, SMARCA4, TSC2, DNM2, TERT
##
## Information transfer
##
## GL ---> TERT
## GL ---> SMARCA4
## GL ---> TSC2
## TERT ---> KRAS
## TERT ---> DNM2
##
## Tree score 1
##
## $fit$phylogenies$CRUK0058
## [ ctree - ctree rank 1/1 for CRUK0058 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.98 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: TP53, EGFR
##
## Information transfer
##
## GL ---> EGFR
## EGFR ---> TP53
##
## Tree score 1
##
## $fit$phylogenies$CRUK0059
## [ ctree - ctree rank 1/1 for CRUK0059 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: KRAS
##
## Information transfer
##
## GL ---> KRAS
##
## Tree score 1
##
## $fit$phylogenies$CRUK0060
## [ ctree - ctree rank 1/1 for CRUK0060 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 5
## cluster nMuts is.driver is.clonal R1
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 11 TRUE TRUE 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1] :: SERPINB13, ARID2, COL5A2, FANCM, PHOX2B, COL2A1, RASA1, NF1, NCOA6, NOTCH2, KMT2C
##
## Information transfer
##
## GL ---> NCOA6
## GL ---> NF1
## GL ---> SERPINB13
## GL ---> ARID2
## GL ---> PHOX2B
## GL ---> COL2A1
## GL ---> RASA1
## GL ---> NOTCH2
## GL ---> KMT2C
## NCOA6 ---> COL5A2
## NF1 ---> FANCM
## SERPINB13 ---> COL5A2
##
## Tree score 1
##
## $fit$phylogenies$CRUK0061
## [ ctree - ctree rank 1/1 for CRUK0061 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: STK11
##
## Information transfer
##
## GL ---> STK11
##
## Tree score 1
##
## $fit$phylogenies$CRUK0062
## [ ctree - ctree rank 1/2 for CRUK0062 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 4 x 11
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5 R6
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 4 4 TRUE TRUE 0.99 0.99 0.98 0.97 0.99 0.99
## 2 1 1 TRUE FALSE 0 0.01 0 0 0 0.94
## 3 16 1 TRUE FALSE 0.93 0.86 0.08 0.02 0.12 0
## 4 2 1 TRUE FALSE 0.84 0.83 0.02 0 0 0
## # … with 1 more variable: R7 <dbl>
##
## Tree shape (drivers annotated)
##
## \-GL
## \-4 :: TP53, PIK3CA, SOX2, CCND1
## |-16 :: UBR5
## | \-2 :: PLXNB2
## \-1 :: FAS
##
## Information transfer
##
## GL ---> TP53
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> CCND1
## TP53 ---> UBR5
## PIK3CA ---> UBR5
## SOX2 ---> UBR5
## CCND1 ---> UBR5
## TP53 ---> FAS
## PIK3CA ---> FAS
## SOX2 ---> FAS
## CCND1 ---> FAS
## UBR5 ---> PLXNB2
##
## Tree score 0.75
##
## $fit$phylogenies$CRUK0063
## [ ctree - ctree rank 1/6 for CRUK0063 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 4 x 9
## cluster nMuts is.driver is.clonal R3 R4 R5 R6 R7
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2 7 TRUE TRUE 0.93 0.99 0.99 0.99 1
## 2 1 2 TRUE FALSE 0 0.99 0.99 0.98 1
## 3 10 1 TRUE FALSE 0 0.99 0.99 0.98 1
## 4 6 1 TRUE FALSE 0 0.02 0.7 0.36 0.55
##
## Tree shape (drivers annotated)
##
## \-GL
## \-2 [R3] :: PIK3CA, TP53, FBXW7, CDKN2A, SOX2, TERT, PRF1
## \-10 :: EP300
## \-1 :: NF1, CYLD
## \-6 :: FANCM
##
## Information transfer
##
## GL ---> CDKN2A
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> FBXW7
## GL ---> PRF1
## CDKN2A ---> TP53
## PIK3CA ---> TERT
## SOX2 ---> TERT
## TP53 ---> TERT
## FBXW7 ---> EP300
## TERT ---> EP300
## PRF1 ---> EP300
## EP300 ---> NF1
## EP300 ---> CYLD
## NF1 ---> FANCM
## CYLD ---> FANCM
##
## Tree score 0.125
##
## $fit$phylogenies$CRUK0064
## [ ctree - ctree rank 1/1 for CRUK0064 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 2 2 TRUE FALSE 0.64 0.11
## 2 1 1 TRUE TRUE 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53
## \-2 :: MLH1, FAT1
##
## Information transfer
##
## GL ---> TP53
## TP53 ---> MLH1
## TP53 ---> FAT1
##
## Tree score 1
##
## $fit$phylogenies$CRUK0065
## [ ctree - ctree rank 1/1 for CRUK0065 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 3 x 10
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5 R6
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 0.99 0.99 1 1 1
## 2 2 3 TRUE FALSE 0 0 0 0 0.48 0
## 3 6 2 TRUE FALSE 0 0 0 0 0.01 0.83
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: TP53, NFE2L2, PIK3CA, SOX2
## |-2 :: MLH1, PTPRC, UBR5
## \-6 :: NOTCH1, NCOA6
##
## Information transfer
##
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> TP53
## PIK3CA ---> NFE2L2
## SOX2 ---> NFE2L2
## TP53 ---> NFE2L2
## NFE2L2 ---> MLH1
## NFE2L2 ---> PTPRC
## NFE2L2 ---> UBR5
## NFE2L2 ---> NOTCH1
## NFE2L2 ---> NCOA6
##
## Tree score 1
##
## $fit$phylogenies$CRUK0066
## [ ctree - ctree rank 1/1 for CRUK0066 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 7 TRUE TRUE 0.99 1 1 0.99
## 2 9 1 TRUE FALSE 0 0.91 0.01 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R4] :: TP53, NOTCH1, CDKN2A, WRN, PDGFRA, TERT, NCOA6
## \-9 :: COL5A2
##
## Information transfer
##
## GL ---> CDKN2A
## GL ---> WRN
## GL ---> PDGFRA
## CDKN2A ---> TP53
## TP53 ---> NOTCH1
## TP53 ---> TERT
## TP53 ---> NCOA6
## WRN ---> TP53
## NOTCH1 ---> COL5A2
## PDGFRA ---> COL5A2
## TERT ---> COL5A2
## NCOA6 ---> COL5A2
##
## Tree score 1
##
## $fit$phylogenies$CRUK0067
## [ ctree - ctree rank 1/1 for CRUK0067 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 0.99 1
## 2 2 1 TRUE FALSE 0.61 0.83
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: NOTCH1, TP53, PIK3CA, SOX2, CDKN2A
## \-2 :: NFE2L2
##
## Information transfer
##
## GL ---> CDKN2A
## GL ---> PIK3CA
## GL ---> SOX2
## CDKN2A ---> TP53
## PIK3CA ---> NOTCH1
## SOX2 ---> NOTCH1
## TP53 ---> NOTCH1
## NOTCH1 ---> NFE2L2
##
## Tree score 1
##
## $fit$phylogenies$CRUK0068
## [ ctree - ctree rank 1/1 for CRUK0068 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 4 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 0.99 1 1 1
## 2 3 1 TRUE FALSE 0.5 0 0 0
## 3 4 1 TRUE FALSE 0.98 0.37 0.99 0.01
## 4 9 1 TRUE FALSE 0 0 0 0.69
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53, PTEN, KMT2D, PIK3CA, SOX2
## |-4 :: SETD2
## | \-3 :: MGA
## \-9 :: TERT
##
## Information transfer
##
## GL ---> TP53
## GL ---> PTEN
## GL ---> KMT2D
## GL ---> PIK3CA
## GL ---> SOX2
## TP53 ---> SETD2
## PTEN ---> SETD2
## KMT2D ---> SETD2
## PIK3CA ---> SETD2
## SOX2 ---> SETD2
## TP53 ---> TERT
## PTEN ---> TERT
## KMT2D ---> TERT
## PIK3CA ---> TERT
## SOX2 ---> TERT
## SETD2 ---> MGA
##
## Tree score 1
##
## $fit$phylogenies$CRUK0069
## [ ctree - ctree rank 1/1 for CRUK0069 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 9
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1 1
## 2 13 1 TRUE FALSE 0.93 0.42 0.32 0.94 0.96
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53, FAT1, PDGFRA, FGFR1
## \-13 :: KRAS
##
## Information transfer
##
## GL ---> TP53
## GL ---> PDGFRA
## GL ---> FGFR1
## TP53 ---> FAT1
## FAT1 ---> KRAS
## PDGFRA ---> KRAS
## FGFR1 ---> KRAS
##
## Tree score 1
##
## $fit$phylogenies$CRUK0070
## [ ctree - ctree rank 1/1 for CRUK0070 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 3 x 9
## cluster nMuts is.driver is.clonal R1 R2 R4 R6 R7
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1 1
## 2 2 1 TRUE FALSE 0 0 0 0.95 0.98
## 3 3 1 TRUE FALSE 0.95 0.96 0.98 0 0.01
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: DNM2, TP53, COL5A2, SOX2
## |-3 :: NFE2L2
## \-2 :: CBLB
##
## Information transfer
##
## GL ---> SOX2
## GL ---> TP53
## SOX2 ---> COL5A2
## TP53 ---> DNM2
## TP53 ---> COL5A2
## DNM2 ---> CBLB
## COL5A2 ---> CBLB
## DNM2 ---> NFE2L2
## COL5A2 ---> NFE2L2
##
## Tree score 1
##
## $fit$phylogenies$CRUK0071
## [ ctree - ctree rank 1/1 for CRUK0071 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 10
## cluster nMuts is.driver is.clonal R1 R2 R3 R5 R6 R7
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 1 0.99 1 1 1 1
## 2 4 1 TRUE FALSE 0 0.570 0 0 0 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R3, R5, R6, R7] :: CMTR2, PIK3CA, SOX2
## \-4 :: UBR5
##
## Information transfer
##
## GL ---> CMTR2
## GL ---> PIK3CA
## GL ---> SOX2
## CMTR2 ---> UBR5
## PIK3CA ---> UBR5
## SOX2 ---> UBR5
##
## Tree score 1
##
## $fit$phylogenies$CRUK0072
## [ ctree - ctree rank 1/1 for CRUK0072 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 1 0.99 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R4] :: TP53, NFE2L2, PIK3CA, SOX2, EGFR, MYC
##
## Information transfer
##
## GL ---> EGFR
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> MYC
## EGFR ---> TP53
## PIK3CA ---> NFE2L2
## SOX2 ---> NFE2L2
## TP53 ---> NFE2L2
##
## Tree score 1
##
## $fit$phylogenies$CRUK0073
## [ ctree - ctree rank 1/1 for CRUK0073 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 8 TRUE TRUE 1 1
## 2 2 1 TRUE FALSE 0 0.93
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1] :: CDKN2A, DICER1, NFE2L2, FAT1, KMT2D, NOTCH2, FGFR1, MYC
## \-2 :: PLXNB2
##
## Information transfer
##
## GL ---> CDKN2A
## GL ---> FAT1
## GL ---> FGFR1
## GL ---> DICER1
## GL ---> NOTCH2
## GL ---> MYC
## CDKN2A ---> NFE2L2
## CDKN2A ---> KMT2D
## FAT1 ---> NFE2L2
## FGFR1 ---> NFE2L2
## DICER1 ---> PLXNB2
## NFE2L2 ---> PLXNB2
## KMT2D ---> PLXNB2
## NOTCH2 ---> PLXNB2
## MYC ---> PLXNB2
##
## Tree score 1
##
## $fit$phylogenies$CRUK0074
## [ ctree - ctree rank 1/1 for CRUK0074 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 0.99 1
## 2 3 1 TRUE FALSE 0 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1] :: TP53, NFE2L2, PIK3CA, SOX2, CCND1
## \-3 :: UBR5
##
## Information transfer
##
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> TP53
## GL ---> CCND1
## PIK3CA ---> NFE2L2
## SOX2 ---> NFE2L2
## TP53 ---> NFE2L2
## NFE2L2 ---> UBR5
## CCND1 ---> UBR5
##
## Tree score 1
##
## $fit$phylogenies$CRUK0075
## [ ctree - ctree rank 1/1 for CRUK0075 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 7 TRUE TRUE 1 0.99
## 2 2 1 TRUE FALSE 0.15 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: NOTCH1, RASA1, TP53, FAT1, MGA, PIK3CA, FGFR1
## \-2 :: NFE2L2
##
## Information transfer
##
## GL ---> PIK3CA
## GL ---> RASA1
## GL ---> MGA
## GL ---> FGFR1
## PIK3CA ---> NOTCH1
## RASA1 ---> TP53
## TP53 ---> NOTCH1
## TP53 ---> FAT1
## NOTCH1 ---> NFE2L2
## FAT1 ---> NFE2L2
## MGA ---> NFE2L2
## FGFR1 ---> NFE2L2
##
## Tree score 1
##
## $fit$phylogenies$CRUK0076
## [ ctree - ctree rank 1/3 for CRUK0076 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 3 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 1 1 1 1
## 2 2 1 TRUE FALSE 0.93 0 0.28 0
## 3 3 1 TRUE FALSE 0.93 0 0.81 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R2, R4] :: SERPINB13, TP53, ARID1B, PIK3CA, SOX2, FGFR1
## \-3 :: COL5A2
## \-2 :: NCOR1
##
## Information transfer
##
## GL ---> TP53
## GL ---> SERPINB13
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> FGFR1
## TP53 ---> ARID1B
## SERPINB13 ---> COL5A2
## ARID1B ---> COL5A2
## PIK3CA ---> COL5A2
## SOX2 ---> COL5A2
## FGFR1 ---> COL5A2
## COL5A2 ---> NCOR1
##
## Tree score 0.444444444444444
##
## $fit$phylogenies$CRUK0077
## [ ctree - ctree rank 1/1 for CRUK0077 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 1 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: TP53, LATS1, KEAP1
##
## Information transfer
##
## GL ---> TP53
## GL ---> KEAP1
## TP53 ---> LATS1
##
## Tree score 1
##
## $fit$phylogenies$CRUK0078
## [ ctree - ctree rank 1/1 for CRUK0078 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R2, R3, R4] :: PLXNB2, PTEN, PIK3CA, SOX2, FGFR1
##
## Information transfer
##
## GL ---> FGFR1
## GL ---> PTEN
## GL ---> PIK3CA
## GL ---> SOX2
## FGFR1 ---> PLXNB2
##
## Tree score 1
##
## $fit$phylogenies$CRUK0079
## [ ctree - ctree rank 1/1 for CRUK0079 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 1 0.99 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: FAT1, TP53, POLE, PIK3CA, SOX2, FGFR1
##
## Information transfer
##
## GL ---> TP53
## GL ---> POLE
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> FGFR1
## TP53 ---> FAT1
##
## Tree score 1
##
## $fit$phylogenies$CRUK0080
## [ ctree - ctree rank 1/1 for CRUK0080 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal R3 R4 R5 R6
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1
## 2 3 1 TRUE FALSE 0 0 0.97 0.83
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R3, R4] :: TP53, WT1, EGFR, CCND1
## \-3 :: IKZF1
##
## Information transfer
##
## GL ---> EGFR
## GL ---> WT1
## GL ---> CCND1
## EGFR ---> TP53
## TP53 ---> IKZF1
## WT1 ---> IKZF1
## CCND1 ---> IKZF1
##
## Tree score 1
##
## $fit$phylogenies$CRUK0081
## [ ctree - ctree rank 1/1 for CRUK0081 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R5
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 1 0.99
## 2 3 1 TRUE FALSE 0.93 0.01
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: NOTCH1, TP53, CDKN2A, FAT1, FANCC
## \-3 :: CYLD
##
## Information transfer
##
## GL ---> CDKN2A
## CDKN2A ---> TP53
## TP53 ---> NOTCH1
## TP53 ---> FAT1
## TP53 ---> FANCC
## NOTCH1 ---> CYLD
## FAT1 ---> CYLD
## FANCC ---> CYLD
##
## Tree score 1
##
## $fit$phylogenies$CRUK0082
## [ ctree - ctree rank 1/1 for CRUK0082 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 9
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 8 TRUE TRUE 1 1 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4, R5] :: TP53, WT1, PTEN, COL5A2, KMT2D, PIK3CA, SOX2, FGFR1
##
## Information transfer
##
## GL ---> FGFR1
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> TP53
## GL ---> WT1
## GL ---> PTEN
## GL ---> KMT2D
## FGFR1 ---> COL5A2
## PIK3CA ---> COL5A2
## SOX2 ---> COL5A2
## TP53 ---> COL5A2
##
## Tree score 1
##
## $fit$phylogenies$CRUK0083
## [ ctree - ctree rank 1/1 for CRUK0083 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 7 TRUE TRUE 1 1 1 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: TP53, FBXW7, RASA1, PIK3CA, SOX2, FGFR1, MYC
##
## Information transfer
##
## GL ---> RASA1
## GL ---> FBXW7
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> FGFR1
## GL ---> MYC
## RASA1 ---> TP53
##
## Tree score 1
##
## $fit$phylogenies$CRUK0084
## [ ctree - ctree rank 1/1 for CRUK0084 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 1 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: CREBBP
##
## Information transfer
##
## GL ---> CREBBP
##
## Tree score 1
##
## $fit$phylogenies$CRUK0085
## [ ctree - ctree rank 1/1 for CRUK0085 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: CHEK2, CREBBP, LATS1, FANCM
##
## Information transfer
##
## GL ---> CHEK2
## GL ---> CREBBP
## GL ---> LATS1
## GL ---> FANCM
##
## Tree score 1
##
## $fit$phylogenies$CRUK0086
## [ ctree - ctree rank 1/1 for CRUK0086 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R4] :: TP53, ARID2, FAT1
##
## Information transfer
##
## GL ---> TP53
## GL ---> ARID2
## TP53 ---> FAT1
##
## Tree score 1
##
## $fit$phylogenies$CRUK0087
## [ ctree - ctree rank 1/1 for CRUK0087 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3] :: NFE2L2, TP53, ASXL1, PIK3CA
##
## Information transfer
##
## GL ---> PIK3CA
## GL ---> TP53
## GL ---> ASXL1
## PIK3CA ---> NFE2L2
## TP53 ---> NFE2L2
##
## Tree score 1
##
## $fit$phylogenies$CRUK0088
## [ ctree - ctree rank 1/1 for CRUK0088 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: CUX1, TP53
##
## Information transfer
##
## GL ---> CUX1
## GL ---> TP53
##
## Tree score 1
##
## $fit$phylogenies$CRUK0089
## [ ctree - ctree rank 1/1 for CRUK0089 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 5
## cluster nMuts is.driver is.clonal R2
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 3 TRUE TRUE 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R2] :: PIK3CA, SMAD4, KEAP1
##
## Information transfer
##
## GL ---> PIK3CA
## GL ---> SMAD4
## GL ---> KEAP1
##
## Tree score 1
##
## $fit$phylogenies$CRUK0090
## [ ctree - ctree rank 1/1 for CRUK0090 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: CDKN2A, NCOA6, CUX1, COL2A1, NRAS
##
## Information transfer
##
## GL ---> CDKN2A
## GL ---> NCOA6
## GL ---> CUX1
## GL ---> COL2A1
## GL ---> NRAS
##
## Tree score 1
##
## $fit$phylogenies$CRUK0091
## [ ctree - ctree rank 1/1 for CRUK0091 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 5
## cluster nMuts is.driver is.clonal R2
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 3 TRUE TRUE 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R2] :: TP53, SMARCA4, CDKN2A
##
## Information transfer
##
## GL ---> CDKN2A
## GL ---> SMARCA4
## CDKN2A ---> TP53
##
## Tree score 1
##
## $fit$phylogenies$CRUK0092
## [ ctree - ctree rank 1/1 for CRUK0092 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 5
## cluster nMuts is.driver is.clonal R1
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 5 TRUE TRUE 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1] :: TP53, SMAD4, RASA1, CBLB, PIK3CA
##
## Information transfer
##
## GL ---> RASA1
## GL ---> PIK3CA
## RASA1 ---> TP53
## TP53 ---> SMAD4
## TP53 ---> CBLB
##
## Tree score 1
##
## $fit$phylogenies$CRUK0093
## [ ctree - ctree rank 1/1 for CRUK0093 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 5
## cluster nMuts is.driver is.clonal R1
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 7 TRUE TRUE 0.96
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1] :: DICER1, CDKN2A, COL2A1, GATA3, CIC, COL5A2, TP53
##
## Information transfer
##
## GL ---> CDKN2A
## GL ---> DICER1
## GL ---> COL2A1
## GL ---> GATA3
## CDKN2A ---> TP53
## CDKN2A ---> COL5A2
## TP53 ---> CIC
## TP53 ---> COL5A2
##
## Tree score 1
##
## $fit$phylogenies$CRUK0094
## [ ctree - ctree rank 1/1 for CRUK0094 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.98 0.98 0.97 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: SMARCA4, TERT
##
## Information transfer
##
## GL ---> SMARCA4
## GL ---> TERT
##
## Tree score 1
##
## $fit$phylogenies$CRUK0095
## [ ctree - ctree rank 1/1 for CRUK0095 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.99 0.99 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3] :: TP53, NF1, RASA1
##
## Information transfer
##
## GL ---> RASA1
## RASA1 ---> TP53
## TP53 ---> NF1
##
## Tree score 1
##
## $fit$phylogenies$CRUK0096
## [ ctree - ctree rank 1/1 for CRUK0096 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 11
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5 R6
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 1 1 1 1 1 1
## # … with 1 more variable: R7 <dbl>
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4, R5, R6, R7] :: KRAS, SGK223, MAP3K1
##
## Information transfer
##
## GL ---> KRAS
## GL ---> SGK223
## GL ---> MAP3K1
##
## Tree score 1
##
## $fit$phylogenies$CRUK0097
## [ ctree - ctree rank 1/1 for CRUK0097 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.995 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: TP53, PTEN
##
## Information transfer
##
## GL ---> TP53
## GL ---> PTEN
##
## Tree score 1
##
## $fit$phylogenies$CRUK0098
## [ ctree - ctree rank 1/1 for CRUK0098 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 1 1 1
## 2 3 1 TRUE FALSE 0.96 0.91 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R3] :: TP53, PTEN
## \-3 :: UBR5
##
## Information transfer
##
## GL ---> TP53
## GL ---> PTEN
## TP53 ---> UBR5
## PTEN ---> UBR5
##
## Tree score 1
##
## $fit$phylogenies$CRUK0099
## [ ctree - ctree rank 1/1 for CRUK0099 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R3 R6 R7
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.95 0.97 0.91 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R3, R6, R7] :: STK11, KEAP1, TP53
##
## Information transfer
##
## GL ---> STK11
## GL ---> KEAP1
## GL ---> TP53
##
## Tree score 1
##
## $fit$phylogenies$CRUK0100
## [ ctree - ctree rank 1/1 for CRUK0100 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3] :: TP53, PHOX2B, COL5A2, STK11, SPEN, CDKN2A
##
## Information transfer
##
## GL ---> CDKN2A
## GL ---> PHOX2B
## GL ---> STK11
## GL ---> SPEN
## CDKN2A ---> TP53
## CDKN2A ---> COL5A2
## TP53 ---> COL5A2
##
## Tree score 1
##
##
## $fit$clones_to_expand
## $fit$clones_to_expand$CRUK0001
## $fit$clones_to_expand$CRUK0001$`1`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 NF1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0001$`2`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 ARHGAP35
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0001$`3`
## # A tbl_graph: 4 nodes and 2 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 4 x 1 (active)
## cluster
## <chr>
## 1 EGFR
## 2 WRN
## 3 TP53
## 4 MGA
## #
## # Edge Data: 2 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 3 1 0.5
## 2 2 3 1 0.5
##
## $fit$clones_to_expand$CRUK0001$`5`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 PASK
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0002
## $fit$clones_to_expand$CRUK0002$`1`
## # A tbl_graph: 3 nodes and 0 edges
## #
## # A rooted forest with 3 trees
## #
## # Node Data: 3 x 1 (active)
## cluster
## <chr>
## 1 RB1
## 2 IKZF1
## 3 KRAS
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0002$`2`
## # A tbl_graph: 2 nodes and 1 edges
## #
## # A rooted tree
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 MET
## 2 TERT
## #
## # Edge Data: 1 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
##
## $fit$clones_to_expand$CRUK0002$`5`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 NF1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0002$`6`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 EP300
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0003
## $fit$clones_to_expand$CRUK0003$`1`
## # A tbl_graph: 3 nodes and 0 edges
## #
## # A rooted forest with 3 trees
## #
## # Node Data: 3 x 1 (active)
## cluster
## <chr>
## 1 PIK3CA
## 2 EGFR
## 3 CDKN2A
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0003$`4`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 CTNNB1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0004
## $fit$clones_to_expand$CRUK0004$`1`
## # A tbl_graph: 2 nodes and 0 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 SMAD4
## 2 NOTCH1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0004$`2`
## # A tbl_graph: 2 nodes and 1 edges
## #
## # A rooted tree
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 EGFR
## 2 TP53
## #
## # Edge Data: 1 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
##
##
## $fit$clones_to_expand$CRUK0005
## $fit$clones_to_expand$CRUK0005$`1`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 NRAS
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0005$`2`
## # A tbl_graph: 5 nodes and 2 edges
## #
## # A rooted forest with 3 trees
## #
## # Node Data: 5 x 1 (active)
## cluster
## <chr>
## 1 BRAF
## 2 TP53
## 3 CMTR2
## 4 PASK
## 5 TERT
## #
## # Edge Data: 2 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 5 1 0.333
## 2 2 5 2 0.667
##
##
## $fit$clones_to_expand$CRUK0006
## $fit$clones_to_expand$CRUK0006$`1`
## # A tbl_graph: 4 nodes and 2 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 4 x 1 (active)
## cluster
## <chr>
## 1 TP53
## 2 PLXNB2
## 3 KEAP1
## 4 TERT
## #
## # Edge Data: 2 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
## 2 1 4 2 1
##
## $fit$clones_to_expand$CRUK0006$`2`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 MAP3K1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0006$`7`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 FANCC
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0007
## $fit$clones_to_expand$CRUK0007$`1`
## # A tbl_graph: 3 nodes and 0 edges
## #
## # A rooted forest with 3 trees
## #
## # Node Data: 3 x 1 (active)
## cluster
## <chr>
## 1 PIK3CA
## 2 EGFR
## 3 SGK223
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0008
## $fit$clones_to_expand$CRUK0008$`2`
## # A tbl_graph: 5 nodes and 0 edges
## #
## # A rooted forest with 5 trees
## #
## # Node Data: 5 x 1 (active)
## cluster
## <chr>
## 1 KEAP1
## 2 STK11
## 3 PRDM1
## 4 U2AF1
## 5 MYC
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0008$`3`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 ARID2
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0009
## $fit$clones_to_expand$CRUK0009$`1`
## # A tbl_graph: 6 nodes and 2 edges
## #
## # A rooted forest with 4 trees
## #
## # Node Data: 6 x 1 (active)
## cluster
## <chr>
## 1 TP53
## 2 BRAF
## 3 ARHGAP35
## 4 KMT2C
## 5 NFE2L2
## 6 MET
## #
## # Edge Data: 2 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 3 1 1
## 2 1 5 3 1
##
## $fit$clones_to_expand$CRUK0009$`2`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 TERT
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0010
## $fit$clones_to_expand$CRUK0010$`1`
## # A tbl_graph: 3 nodes and 0 edges
## #
## # A rooted forest with 3 trees
## #
## # Node Data: 3 x 1 (active)
## cluster
## <chr>
## 1 SETD2
## 2 EGFR
## 3 TERT
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0011
## $fit$clones_to_expand$CRUK0011$`1`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 KRAS
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0011$`3`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 FLT4
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0012
## $fit$clones_to_expand$CRUK0012$`1`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 EGFR
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0013
## $fit$clones_to_expand$CRUK0013$`1`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 STK11
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0013$`2`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 NOTCH1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0013$`3`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 KRAS
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0013$`4`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 EGFR
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0014
## $fit$clones_to_expand$CRUK0014$`1`
## # A tbl_graph: 2 nodes and 2 edges
## #
## # A directed simple graph with 1 component
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 KRAS
## 2 TP53
## #
## # Edge Data: 2 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
## 2 2 1 2 1
##
## $fit$clones_to_expand$CRUK0014$`2`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 RNF43
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0015
## $fit$clones_to_expand$CRUK0015$`1`
## # A tbl_graph: 2 nodes and 0 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 BAP1
## 2 EGFR
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0015$`2`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 TP53
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0015$`3`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 RB1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0016
## $fit$clones_to_expand$CRUK0016$`1`
## # A tbl_graph: 6 nodes and 4 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 6 x 1 (active)
## cluster
## <chr>
## 1 CDKN2A
## 2 TP53
## 3 FAT1
## 4 SPEN
## 5 CBLB
## 6 TERT
## #
## # Edge Data: 4 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
## 2 2 5 1 1
## 3 2 3 1 1
## # … with 1 more row
##
## $fit$clones_to_expand$CRUK0016$`2`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 ASXL1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0016$`6`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 PTPRC
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0016$`10`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 DNM2
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0016$`16`
## # A tbl_graph: 2 nodes and 0 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 LATS1
## 2 ARID1B
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0017
## $fit$clones_to_expand$CRUK0017$`1`
## # A tbl_graph: 5 nodes and 3 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 5 x 1 (active)
## cluster
## <chr>
## 1 KEAP1
## 2 MYC
## 3 TP53
## 4 ARID1B
## 5 ARID2
## #
## # Edge Data: 3 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 5 1 0.5
## 2 2 5 1 0.5
## 3 3 4 1 1
##
## $fit$clones_to_expand$CRUK0017$`3`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 KRAS
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0018
## $fit$clones_to_expand$CRUK0018$`1`
## # A tbl_graph: 4 nodes and 1 edges
## #
## # A rooted forest with 3 trees
## #
## # Node Data: 4 x 1 (active)
## cluster
## <chr>
## 1 KRAS
## 2 CMTR2
## 3 MGA
## 4 COL5A2
## #
## # Edge Data: 1 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 3 1 1
##
##
## $fit$clones_to_expand$CRUK0019
## $fit$clones_to_expand$CRUK0019$`1`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 EGFR
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0020
## $fit$clones_to_expand$CRUK0020$`1`
## # A tbl_graph: 7 nodes and 6 edges
## #
## # A directed simple graph with 3 components
## #
## # Node Data: 7 x 1 (active)
## cluster
## <chr>
## 1 ARID2
## 2 KEAP1
## 3 KRAS
## 4 TP53
## 5 MGA
## 6 COL2A1
## # … with 1 more row
## #
## # Edge Data: 6 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 3 1 0.25
## 2 2 1 1 1
## 3 2 3 1 0.25
## # … with 3 more rows
##
## $fit$clones_to_expand$CRUK0020$`2`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 PIK3CA
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0020$`3`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 BAP1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0020$`4`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 NCOR1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0021
## $fit$clones_to_expand$CRUK0021$`1`
## # A tbl_graph: 4 nodes and 2 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 4 x 1 (active)
## cluster
## <chr>
## 1 CDKN2A
## 2 EGFR
## 3 TP53
## 4 CHEK2
## #
## # Edge Data: 2 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 3 1 0.5
## 2 2 3 1 0.5
##
##
## $fit$clones_to_expand$CRUK0022
## $fit$clones_to_expand$CRUK0022$`1`
## # A tbl_graph: 2 nodes and 1 edges
## #
## # A rooted tree
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 EGFR
## 2 TP53
## #
## # Edge Data: 1 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
##
## $fit$clones_to_expand$CRUK0022$`2`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 CIC
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0023
## $fit$clones_to_expand$CRUK0023$`1`
## # A tbl_graph: 3 nodes and 0 edges
## #
## # A rooted forest with 3 trees
## #
## # Node Data: 3 x 1 (active)
## cluster
## <chr>
## 1 WRN
## 2 KRAS
## 3 CDKN2A
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0023$`2`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 TP53
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0023$`4`
## # A tbl_graph: 2 nodes and 0 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 PTPRC
## 2 KMT2D
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0024
## $fit$clones_to_expand$CRUK0024$`1`
## # A tbl_graph: 4 nodes and 2 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 4 x 1 (active)
## cluster
## <chr>
## 1 EGFR
## 2 STK11
## 3 TP53
## 4 POLE
## #
## # Edge Data: 2 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 3 1 1
## 2 2 1 1 1
##
## $fit$clones_to_expand$CRUK0024$`3`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 ATM
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0024$`4`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 NCOR1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0025
## $fit$clones_to_expand$CRUK0025$`1`
## # A tbl_graph: 3 nodes and 3 edges
## #
## # A directed simple graph with 1 component
## #
## # Node Data: 3 x 1 (active)
## cluster
## <chr>
## 1 KRAS
## 2 TP53
## 3 MGA
## #
## # Edge Data: 3 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 3 1 1
## 2 1 2 1 1
## 3 2 1 2 1
##
##
## $fit$clones_to_expand$CRUK0026
## $fit$clones_to_expand$CRUK0026$`1`
## # A tbl_graph: 4 nodes and 2 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 4 x 1 (active)
## cluster
## <chr>
## 1 EGFR
## 2 TP53
## 3 RB1
## 4 SERPINB13
## #
## # Edge Data: 2 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 3 1 1
## 2 1 2 1 1
##
##
## $fit$clones_to_expand$CRUK0027
## $fit$clones_to_expand$CRUK0027$`1`
## # A tbl_graph: 2 nodes and 2 edges
## #
## # A directed simple graph with 1 component
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 KRAS
## 2 TP53
## #
## # Edge Data: 2 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
## 2 2 1 2 1
##
## $fit$clones_to_expand$CRUK0027$`2`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 PLXNB2
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0028
## $fit$clones_to_expand$CRUK0028$`1`
## # A tbl_graph: 2 nodes and 0 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 APC
## 2 EGFR
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0029
## $fit$clones_to_expand$CRUK0029$`1`
## # A tbl_graph: 4 nodes and 1 edges
## #
## # A rooted forest with 3 trees
## #
## # Node Data: 4 x 1 (active)
## cluster
## <chr>
## 1 TP53
## 2 NRAS
## 3 MGA
## 4 CCND1
## #
## # Edge Data: 1 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
##
##
## $fit$clones_to_expand$CRUK0030
## $fit$clones_to_expand$CRUK0030$`1`
## # A tbl_graph: 6 nodes and 3 edges
## #
## # A directed simple graph with 4 components
## #
## # Node Data: 6 x 1 (active)
## cluster
## <chr>
## 1 KRAS
## 2 TP53
## 3 TSC2
## 4 U2AF1
## 5 FBXW7
## 6 NF1
## #
## # Edge Data: 3 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
## 2 2 1 2 1
## 3 2 6 1 1
##
##
## $fit$clones_to_expand$CRUK0031
## $fit$clones_to_expand$CRUK0031$`1`
## # A tbl_graph: 4 nodes and 0 edges
## #
## # A rooted forest with 4 trees
## #
## # Node Data: 4 x 1 (active)
## cluster
## <chr>
## 1 KEAP1
## 2 CDKN2A
## 3 PRF1
## 4 FGFR1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0031$`6`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 NF1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0032
## $fit$clones_to_expand$CRUK0032$`1`
## # A tbl_graph: 4 nodes and 0 edges
## #
## # A rooted forest with 4 trees
## #
## # Node Data: 4 x 1 (active)
## cluster
## <chr>
## 1 ATM
## 2 RAD21
## 3 U2AF1
## 4 RNF43
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0032$`4`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 CCND1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0032$`6`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 ARID1B
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0033
## $fit$clones_to_expand$CRUK0033$`1`
## # A tbl_graph: 2 nodes and 0 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 KEAP1
## 2 CTNNB1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0034
## $fit$clones_to_expand$CRUK0034$`1`
## # A tbl_graph: 3 nodes and 1 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 3 x 1 (active)
## cluster
## <chr>
## 1 KRAS
## 2 ATM
## 3 PLXNB2
## #
## # Edge Data: 1 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 3 1 1
##
## $fit$clones_to_expand$CRUK0034$`4`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 MGA
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0035
## $fit$clones_to_expand$CRUK0035$`1`
## # A tbl_graph: 2 nodes and 1 edges
## #
## # A rooted tree
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 TP53
## 2 FAS
## #
## # Edge Data: 1 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
##
## $fit$clones_to_expand$CRUK0035$`4`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 FLT4
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0036
## $fit$clones_to_expand$CRUK0036$`1`
## # A tbl_graph: 5 nodes and 4 edges
## #
## # A rooted tree
## #
## # Node Data: 5 x 1 (active)
## cluster
## <chr>
## 1 ARHGAP35
## 2 KEAP1
## 3 PIK3CA
## 4 TERT
## 5 KRAS
## #
## # Edge Data: 4 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 4 1 0.5
## 2 2 5 1 0.5
## 3 3 4 1 0.5
## # … with 1 more row
##
##
## $fit$clones_to_expand$CRUK0037
## $fit$clones_to_expand$CRUK0037$`1`
## # A tbl_graph: 3 nodes and 0 edges
## #
## # A rooted forest with 3 trees
## #
## # Node Data: 3 x 1 (active)
## cluster
## <chr>
## 1 NCOA6
## 2 CREBBP
## 3 KRAS
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0038
## $fit$clones_to_expand$CRUK0038$`1`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 KRAS
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0038$`3`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 KMT2D
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0039
## $fit$clones_to_expand$CRUK0039$`1`
## # A tbl_graph: 4 nodes and 0 edges
## #
## # A rooted forest with 4 trees
## #
## # Node Data: 4 x 1 (active)
## cluster
## <chr>
## 1 KRAS
## 2 CMTR2
## 3 NF1
## 4 PHOX2B
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0040
## $fit$clones_to_expand$CRUK0040$`1`
## # A tbl_graph: 4 nodes and 1 edges
## #
## # A rooted forest with 3 trees
## #
## # Node Data: 4 x 1 (active)
## cluster
## <chr>
## 1 KRAS
## 2 NCOR1
## 3 RAD21
## 4 GATA3
## #
## # Edge Data: 1 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
##
##
## $fit$clones_to_expand$CRUK0041
## $fit$clones_to_expand$CRUK0041$`1`
## # A tbl_graph: 3 nodes and 1 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 3 x 1 (active)
## cluster
## <chr>
## 1 BRAF
## 2 TERT
## 3 EGFR
## #
## # Edge Data: 1 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
##
##
## $fit$clones_to_expand$CRUK0042
## $fit$clones_to_expand$CRUK0042$`1`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 KRAS
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0043
## $fit$clones_to_expand$CRUK0043$`1`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 MET
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0044
## $fit$clones_to_expand$CRUK0044$`1`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 KRAS
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0045
## $fit$clones_to_expand$CRUK0045$`1`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 BAP1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0046
## $fit$clones_to_expand$CRUK0046$`1`
## # A tbl_graph: 2 nodes and 0 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 KEAP1
## 2 APC
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0047
## $fit$clones_to_expand$CRUK0047$`1`
## # A tbl_graph: 4 nodes and 2 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 4 x 1 (active)
## cluster
## <chr>
## 1 MYC
## 2 STK11
## 3 APC
## 4 KRAS
## #
## # Edge Data: 2 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 4 1 0.5
## 2 2 4 1 0.5
##
##
## $fit$clones_to_expand$CRUK0048
## $fit$clones_to_expand$CRUK0048$`1`
## # A tbl_graph: 7 nodes and 3 edges
## #
## # A directed acyclic simple graph with 5 components
## #
## # Node Data: 7 x 1 (active)
## cluster
## <chr>
## 1 EGFR
## 2 TP53
## 3 APC
## 4 PRDM1
## 5 ARHGAP35
## 6 BRAF
## # … with 1 more row
## #
## # Edge Data: 3 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 5 1 0.5
## 2 1 2 1 1
## 3 2 5 1 0.5
##
##
## $fit$clones_to_expand$CRUK0049
## $fit$clones_to_expand$CRUK0049$`1`
## # A tbl_graph: 5 nodes and 4 edges
## #
## # A directed simple graph with 2 components
## #
## # Node Data: 5 x 1 (active)
## cluster
## <chr>
## 1 EGFR
## 2 KRAS
## 3 TP53
## 4 RB1
## 5 COL2A1
## #
## # Edge Data: 4 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 4 1 1
## 2 1 3 1 0.5
## 3 2 3 1 0.5
## # … with 1 more row
##
##
## $fit$clones_to_expand$CRUK0050
## $fit$clones_to_expand$CRUK0050$`1`
## # A tbl_graph: 3 nodes and 2 edges
## #
## # A rooted tree
## #
## # Node Data: 3 x 1 (active)
## cluster
## <chr>
## 1 MYC
## 2 STK11
## 3 KRAS
## #
## # Edge Data: 2 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 3 1 0.5
## 2 2 3 1 0.5
##
##
## $fit$clones_to_expand$CRUK0051
## $fit$clones_to_expand$CRUK0051$`1`
## # A tbl_graph: 4 nodes and 3 edges
## #
## # A directed simple graph with 2 components
## #
## # Node Data: 4 x 1 (active)
## cluster
## <chr>
## 1 EGFR
## 2 KRAS
## 3 TP53
## 4 FBXW7
## #
## # Edge Data: 3 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 3 1 0.5
## 2 2 3 1 0.5
## 3 3 2 2 1
##
## $fit$clones_to_expand$CRUK0051$`3`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 EP300
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0052
## $fit$clones_to_expand$CRUK0052$`1`
## # A tbl_graph: 8 nodes and 8 edges
## #
## # A directed simple graph with 3 components
## #
## # Node Data: 8 x 1 (active)
## cluster
## <chr>
## 1 KEAP1
## 2 KRAS
## 3 MGA
## 4 TP53
## 5 KMT2D
## 6 NOTCH2
## # … with 2 more rows
## #
## # Edge Data: 8 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 0.333
## 2 1 7 1 0.333
## 3 2 5 2 1
## # … with 5 more rows
##
## $fit$clones_to_expand$CRUK0052$`2`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 UBR5
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0054
## $fit$clones_to_expand$CRUK0054$`1`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 EGFR
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0055
## $fit$clones_to_expand$CRUK0055$`1`
## # A tbl_graph: 2 nodes and 0 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 FANCM
## 2 UBR5
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0055$`2`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 FAT1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0056
## $fit$clones_to_expand$CRUK0056$`1`
## # A tbl_graph: 2 nodes and 0 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 RASA1
## 2 CREBBP
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0056$`3`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 TP53
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0057
## $fit$clones_to_expand$CRUK0057$`1`
## # A tbl_graph: 5 nodes and 2 edges
## #
## # A rooted forest with 3 trees
## #
## # Node Data: 5 x 1 (active)
## cluster
## <chr>
## 1 TERT
## 2 KRAS
## 3 SMARCA4
## 4 TSC2
## 5 DNM2
## #
## # Edge Data: 2 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 5 1 1
## 2 1 2 1 1
##
##
## $fit$clones_to_expand$CRUK0058
## $fit$clones_to_expand$CRUK0058$`1`
## # A tbl_graph: 2 nodes and 1 edges
## #
## # A rooted tree
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 EGFR
## 2 TP53
## #
## # Edge Data: 1 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
##
##
## $fit$clones_to_expand$CRUK0059
## $fit$clones_to_expand$CRUK0059$`1`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 KRAS
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0060
## $fit$clones_to_expand$CRUK0060$`1`
## # A tbl_graph: 11 nodes and 3 edges
## #
## # A rooted forest with 8 trees
## #
## # Node Data: 11 x 1 (active)
## cluster
## <chr>
## 1 NCOA6
## 2 NF1
## 3 SERPINB13
## 4 ARID2
## 5 COL5A2
## 6 FANCM
## # … with 5 more rows
## #
## # Edge Data: 3 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 5 1 0.5
## 2 2 6 1 1
## 3 3 5 1 0.5
##
##
## $fit$clones_to_expand$CRUK0061
## $fit$clones_to_expand$CRUK0061$`1`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 STK11
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0062
## $fit$clones_to_expand$CRUK0062$`1`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 FAS
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0062$`2`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 PLXNB2
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0062$`4`
## # A tbl_graph: 4 nodes and 0 edges
## #
## # A rooted forest with 4 trees
## #
## # Node Data: 4 x 1 (active)
## cluster
## <chr>
## 1 TP53
## 2 PIK3CA
## 3 SOX2
## 4 CCND1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0062$`16`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 UBR5
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0063
## $fit$clones_to_expand$CRUK0063$`1`
## # A tbl_graph: 2 nodes and 0 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 NF1
## 2 CYLD
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0063$`2`
## # A tbl_graph: 7 nodes and 4 edges
## #
## # A rooted forest with 3 trees
## #
## # Node Data: 7 x 1 (active)
## cluster
## <chr>
## 1 CDKN2A
## 2 PIK3CA
## 3 SOX2
## 4 TP53
## 5 FBXW7
## 6 TERT
## # … with 1 more row
## #
## # Edge Data: 4 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 4 1 1
## 2 2 6 1 0.25
## 3 3 6 1 0.25
## # … with 1 more row
##
## $fit$clones_to_expand$CRUK0063$`6`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 FANCM
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0063$`10`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 EP300
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0064
## $fit$clones_to_expand$CRUK0064$`1`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 TP53
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0064$`2`
## # A tbl_graph: 2 nodes and 0 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 MLH1
## 2 FAT1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0065
## $fit$clones_to_expand$CRUK0065$`1`
## # A tbl_graph: 4 nodes and 3 edges
## #
## # A rooted tree
## #
## # Node Data: 4 x 1 (active)
## cluster
## <chr>
## 1 PIK3CA
## 2 SOX2
## 3 TP53
## 4 NFE2L2
## #
## # Edge Data: 3 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 4 2 0.286
## 2 2 4 2 0.286
## 3 3 4 3 0.429
##
## $fit$clones_to_expand$CRUK0065$`2`
## # A tbl_graph: 3 nodes and 0 edges
## #
## # A rooted forest with 3 trees
## #
## # Node Data: 3 x 1 (active)
## cluster
## <chr>
## 1 MLH1
## 2 PTPRC
## 3 UBR5
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0065$`6`
## # A tbl_graph: 2 nodes and 0 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 NOTCH1
## 2 NCOA6
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0066
## $fit$clones_to_expand$CRUK0066$`1`
## # A tbl_graph: 7 nodes and 5 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 7 x 1 (active)
## cluster
## <chr>
## 1 CDKN2A
## 2 TP53
## 3 WRN
## 4 NOTCH1
## 5 PDGFRA
## 6 TERT
## # … with 1 more row
## #
## # Edge Data: 5 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 0.5
## 2 2 7 1 1
## 3 2 4 2 1
## # … with 2 more rows
##
## $fit$clones_to_expand$CRUK0066$`9`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 COL5A2
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0067
## $fit$clones_to_expand$CRUK0067$`1`
## # A tbl_graph: 5 nodes and 4 edges
## #
## # A rooted tree
## #
## # Node Data: 5 x 1 (active)
## cluster
## <chr>
## 1 CDKN2A
## 2 PIK3CA
## 3 SOX2
## 4 TP53
## 5 NOTCH1
## #
## # Edge Data: 4 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 4 1 1
## 2 2 5 1 0.25
## 3 3 5 1 0.25
## # … with 1 more row
##
## $fit$clones_to_expand$CRUK0067$`2`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 NFE2L2
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0068
## $fit$clones_to_expand$CRUK0068$`1`
## # A tbl_graph: 5 nodes and 0 edges
## #
## # A rooted forest with 5 trees
## #
## # Node Data: 5 x 1 (active)
## cluster
## <chr>
## 1 TP53
## 2 PTEN
## 3 KMT2D
## 4 PIK3CA
## 5 SOX2
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0068$`3`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 MGA
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0068$`4`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 SETD2
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0068$`9`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 TERT
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0069
## $fit$clones_to_expand$CRUK0069$`1`
## # A tbl_graph: 4 nodes and 1 edges
## #
## # A rooted forest with 3 trees
## #
## # Node Data: 4 x 1 (active)
## cluster
## <chr>
## 1 TP53
## 2 FAT1
## 3 PDGFRA
## 4 FGFR1
## #
## # Edge Data: 1 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
##
## $fit$clones_to_expand$CRUK0069$`13`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 KRAS
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0070
## $fit$clones_to_expand$CRUK0070$`1`
## # A tbl_graph: 4 nodes and 3 edges
## #
## # A rooted tree
## #
## # Node Data: 4 x 1 (active)
## cluster
## <chr>
## 1 SOX2
## 2 TP53
## 3 DNM2
## 4 COL5A2
## #
## # Edge Data: 3 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 4 1 0.333
## 2 2 4 2 0.667
## 3 2 3 1 1
##
## $fit$clones_to_expand$CRUK0070$`2`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 CBLB
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0070$`3`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 NFE2L2
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0071
## $fit$clones_to_expand$CRUK0071$`1`
## # A tbl_graph: 3 nodes and 0 edges
## #
## # A rooted forest with 3 trees
## #
## # Node Data: 3 x 1 (active)
## cluster
## <chr>
## 1 CMTR2
## 2 PIK3CA
## 3 SOX2
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0071$`4`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 UBR5
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0072
## $fit$clones_to_expand$CRUK0072$`1`
## # A tbl_graph: 6 nodes and 4 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 6 x 1 (active)
## cluster
## <chr>
## 1 EGFR
## 2 PIK3CA
## 3 SOX2
## 4 TP53
## 5 NFE2L2
## 6 MYC
## #
## # Edge Data: 4 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 4 1 1
## 2 2 5 2 0.286
## 3 3 5 2 0.286
## # … with 1 more row
##
##
## $fit$clones_to_expand$CRUK0073
## $fit$clones_to_expand$CRUK0073$`1`
## # A tbl_graph: 8 nodes and 4 edges
## #
## # A rooted forest with 4 trees
## #
## # Node Data: 8 x 1 (active)
## cluster
## <chr>
## 1 CDKN2A
## 2 FAT1
## 3 FGFR1
## 4 DICER1
## 5 NFE2L2
## 6 KMT2D
## # … with 2 more rows
## #
## # Edge Data: 4 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 6 1 1
## 2 1 5 1 0.333
## 3 2 5 1 0.333
## # … with 1 more row
##
## $fit$clones_to_expand$CRUK0073$`2`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 PLXNB2
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0074
## $fit$clones_to_expand$CRUK0074$`1`
## # A tbl_graph: 5 nodes and 3 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 5 x 1 (active)
## cluster
## <chr>
## 1 PIK3CA
## 2 SOX2
## 3 TP53
## 4 NFE2L2
## 5 CCND1
## #
## # Edge Data: 3 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 4 2 0.286
## 2 2 4 2 0.286
## 3 3 4 3 0.429
##
## $fit$clones_to_expand$CRUK0074$`3`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 UBR5
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0075
## $fit$clones_to_expand$CRUK0075$`1`
## # A tbl_graph: 7 nodes and 4 edges
## #
## # A rooted forest with 3 trees
## #
## # Node Data: 7 x 1 (active)
## cluster
## <chr>
## 1 PIK3CA
## 2 RASA1
## 3 TP53
## 4 NOTCH1
## 5 FAT1
## 6 MGA
## # … with 1 more row
## #
## # Edge Data: 4 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 4 1 0.333
## 2 2 3 1 1
## 3 3 5 1 1
## # … with 1 more row
##
## $fit$clones_to_expand$CRUK0075$`2`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 NFE2L2
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0076
## $fit$clones_to_expand$CRUK0076$`1`
## # A tbl_graph: 6 nodes and 1 edges
## #
## # A rooted forest with 5 trees
## #
## # Node Data: 6 x 1 (active)
## cluster
## <chr>
## 1 TP53
## 2 SERPINB13
## 3 ARID1B
## 4 PIK3CA
## 5 SOX2
## 6 FGFR1
## #
## # Edge Data: 1 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 3 1 1
##
## $fit$clones_to_expand$CRUK0076$`2`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 NCOR1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0076$`3`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 COL5A2
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0077
## $fit$clones_to_expand$CRUK0077$`1`
## # A tbl_graph: 3 nodes and 1 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 3 x 1 (active)
## cluster
## <chr>
## 1 TP53
## 2 LATS1
## 3 KEAP1
## #
## # Edge Data: 1 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
##
##
## $fit$clones_to_expand$CRUK0078
## $fit$clones_to_expand$CRUK0078$`1`
## # A tbl_graph: 5 nodes and 1 edges
## #
## # A rooted forest with 4 trees
## #
## # Node Data: 5 x 1 (active)
## cluster
## <chr>
## 1 FGFR1
## 2 PLXNB2
## 3 PTEN
## 4 PIK3CA
## 5 SOX2
## #
## # Edge Data: 1 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
##
##
## $fit$clones_to_expand$CRUK0079
## $fit$clones_to_expand$CRUK0079$`1`
## # A tbl_graph: 6 nodes and 1 edges
## #
## # A rooted forest with 5 trees
## #
## # Node Data: 6 x 1 (active)
## cluster
## <chr>
## 1 TP53
## 2 FAT1
## 3 POLE
## 4 PIK3CA
## 5 SOX2
## 6 FGFR1
## #
## # Edge Data: 1 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
##
##
## $fit$clones_to_expand$CRUK0080
## $fit$clones_to_expand$CRUK0080$`1`
## # A tbl_graph: 4 nodes and 1 edges
## #
## # A rooted forest with 3 trees
## #
## # Node Data: 4 x 1 (active)
## cluster
## <chr>
## 1 EGFR
## 2 TP53
## 3 WT1
## 4 CCND1
## #
## # Edge Data: 1 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
##
## $fit$clones_to_expand$CRUK0080$`3`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 IKZF1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0081
## $fit$clones_to_expand$CRUK0081$`1`
## # A tbl_graph: 5 nodes and 4 edges
## #
## # A rooted tree
## #
## # Node Data: 5 x 1 (active)
## cluster
## <chr>
## 1 CDKN2A
## 2 TP53
## 3 NOTCH1
## 4 FAT1
## 5 FANCC
## #
## # Edge Data: 4 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
## 2 2 5 1 1
## 3 2 4 1 1
## # … with 1 more row
##
## $fit$clones_to_expand$CRUK0081$`3`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 CYLD
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0082
## $fit$clones_to_expand$CRUK0082$`1`
## # A tbl_graph: 8 nodes and 4 edges
## #
## # A rooted forest with 4 trees
## #
## # Node Data: 8 x 1 (active)
## cluster
## <chr>
## 1 FGFR1
## 2 PIK3CA
## 3 SOX2
## 4 TP53
## 5 WT1
## 6 PTEN
## # … with 2 more rows
## #
## # Edge Data: 4 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 7 1 0.2
## 2 2 7 1 0.2
## 3 3 7 1 0.2
## # … with 1 more row
##
##
## $fit$clones_to_expand$CRUK0083
## $fit$clones_to_expand$CRUK0083$`1`
## # A tbl_graph: 7 nodes and 1 edges
## #
## # A rooted forest with 6 trees
## #
## # Node Data: 7 x 1 (active)
## cluster
## <chr>
## 1 RASA1
## 2 TP53
## 3 FBXW7
## 4 PIK3CA
## 5 SOX2
## 6 FGFR1
## # … with 1 more row
## #
## # Edge Data: 1 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
##
##
## $fit$clones_to_expand$CRUK0084
## $fit$clones_to_expand$CRUK0084$`1`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 CREBBP
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0085
## $fit$clones_to_expand$CRUK0085$`1`
## # A tbl_graph: 4 nodes and 0 edges
## #
## # A rooted forest with 4 trees
## #
## # Node Data: 4 x 1 (active)
## cluster
## <chr>
## 1 CHEK2
## 2 CREBBP
## 3 LATS1
## 4 FANCM
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0086
## $fit$clones_to_expand$CRUK0086$`1`
## # A tbl_graph: 3 nodes and 1 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 3 x 1 (active)
## cluster
## <chr>
## 1 TP53
## 2 ARID2
## 3 FAT1
## #
## # Edge Data: 1 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 3 1 1
##
##
## $fit$clones_to_expand$CRUK0087
## $fit$clones_to_expand$CRUK0087$`1`
## # A tbl_graph: 4 nodes and 2 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 4 x 1 (active)
## cluster
## <chr>
## 1 PIK3CA
## 2 TP53
## 3 NFE2L2
## 4 ASXL1
## #
## # Edge Data: 2 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 3 2 0.4
## 2 2 3 3 0.6
##
##
## $fit$clones_to_expand$CRUK0088
## $fit$clones_to_expand$CRUK0088$`1`
## # A tbl_graph: 2 nodes and 0 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 CUX1
## 2 TP53
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0089
## $fit$clones_to_expand$CRUK0089$`1`
## # A tbl_graph: 3 nodes and 0 edges
## #
## # A rooted forest with 3 trees
## #
## # Node Data: 3 x 1 (active)
## cluster
## <chr>
## 1 PIK3CA
## 2 SMAD4
## 3 KEAP1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0090
## $fit$clones_to_expand$CRUK0090$`1`
## # A tbl_graph: 5 nodes and 0 edges
## #
## # A rooted forest with 5 trees
## #
## # Node Data: 5 x 1 (active)
## cluster
## <chr>
## 1 CDKN2A
## 2 NCOA6
## 3 CUX1
## 4 COL2A1
## 5 NRAS
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0091
## $fit$clones_to_expand$CRUK0091$`1`
## # A tbl_graph: 3 nodes and 1 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 3 x 1 (active)
## cluster
## <chr>
## 1 CDKN2A
## 2 TP53
## 3 SMARCA4
## #
## # Edge Data: 1 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
##
##
## $fit$clones_to_expand$CRUK0092
## $fit$clones_to_expand$CRUK0092$`1`
## # A tbl_graph: 5 nodes and 3 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 5 x 1 (active)
## cluster
## <chr>
## 1 RASA1
## 2 TP53
## 3 SMAD4
## 4 CBLB
## 5 PIK3CA
## #
## # Edge Data: 3 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
## 2 2 4 1 1
## 3 2 3 1 1
##
##
## $fit$clones_to_expand$CRUK0093
## $fit$clones_to_expand$CRUK0093$`1`
## # A tbl_graph: 7 nodes and 4 edges
## #
## # A directed acyclic simple graph with 4 components
## #
## # Node Data: 7 x 1 (active)
## cluster
## <chr>
## 1 CDKN2A
## 2 TP53
## 3 DICER1
## 4 COL2A1
## 5 GATA3
## 6 CIC
## # … with 1 more row
## #
## # Edge Data: 4 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 7 1 0.333
## 2 1 2 1 1
## 3 2 6 1 1
## # … with 1 more row
##
##
## $fit$clones_to_expand$CRUK0094
## $fit$clones_to_expand$CRUK0094$`1`
## # A tbl_graph: 2 nodes and 0 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 SMARCA4
## 2 TERT
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0095
## $fit$clones_to_expand$CRUK0095$`1`
## # A tbl_graph: 3 nodes and 2 edges
## #
## # A rooted tree
## #
## # Node Data: 3 x 1 (active)
## cluster
## <chr>
## 1 RASA1
## 2 TP53
## 3 NF1
## #
## # Edge Data: 2 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
## 2 2 3 1 1
##
##
## $fit$clones_to_expand$CRUK0096
## $fit$clones_to_expand$CRUK0096$`1`
## # A tbl_graph: 3 nodes and 0 edges
## #
## # A rooted forest with 3 trees
## #
## # Node Data: 3 x 1 (active)
## cluster
## <chr>
## 1 KRAS
## 2 SGK223
## 3 MAP3K1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0097
## $fit$clones_to_expand$CRUK0097$`1`
## # A tbl_graph: 2 nodes and 0 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 TP53
## 2 PTEN
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0098
## $fit$clones_to_expand$CRUK0098$`1`
## # A tbl_graph: 2 nodes and 0 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 TP53
## 2 PTEN
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0098$`3`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 UBR5
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0099
## $fit$clones_to_expand$CRUK0099$`1`
## # A tbl_graph: 3 nodes and 0 edges
## #
## # A rooted forest with 3 trees
## #
## # Node Data: 3 x 1 (active)
## cluster
## <chr>
## 1 STK11
## 2 KEAP1
## 3 TP53
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0100
## $fit$clones_to_expand$CRUK0100$`1`
## # A tbl_graph: 6 nodes and 3 edges
## #
## # A directed acyclic simple graph with 4 components
## #
## # Node Data: 6 x 1 (active)
## cluster
## <chr>
## 1 CDKN2A
## 2 TP53
## 3 PHOX2B
## 4 COL5A2
## 5 STK11
## 6 SPEN
## #
## # Edge Data: 3 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 4 1 0.333
## 2 1 2 1 1
## 3 2 4 2 0.667
##
##
##
## $fit$clones_expansions
## $fit$clones_expansions$CRUK0001
## # A tibble: 10 x 2
## from to
## <chr> <chr>
## 1 GL EGFR
## 2 GL WRN
## 3 GL MGA
## 4 EGFR TP53
## 5 WRN TP53
## 6 TP53 NF1
## 7 MGA NF1
## 8 TP53 ARHGAP35
## 9 MGA ARHGAP35
## 10 NF1 PASK
##
## $fit$clones_expansions$CRUK0002
## # A tibble: 7 x 2
## from to
## <chr> <chr>
## 1 GL MET
## 2 MET TERT
## 3 TERT EP300
## 4 TERT RB1
## 5 TERT IKZF1
## 6 TERT KRAS
## 7 EP300 NF1
##
## $fit$clones_expansions$CRUK0003
## # A tibble: 6 x 2
## from to
## <chr> <chr>
## 1 GL PIK3CA
## 2 GL EGFR
## 3 GL CDKN2A
## 4 PIK3CA CTNNB1
## 5 EGFR CTNNB1
## 6 CDKN2A CTNNB1
##
## $fit$clones_expansions$CRUK0004
## # A tibble: 4 x 2
## from to
## <chr> <chr>
## 1 GL EGFR
## 2 EGFR TP53
## 3 TP53 SMAD4
## 4 TP53 NOTCH1
##
## $fit$clones_expansions$CRUK0005
## # A tibble: 9 x 2
## from to
## <chr> <chr>
## 1 GL BRAF
## 2 GL TP53
## 3 GL CMTR2
## 4 GL PASK
## 5 BRAF TERT
## 6 TP53 TERT
## 7 CMTR2 NRAS
## 8 PASK NRAS
## 9 TERT NRAS
##
## $fit$clones_expansions$CRUK0006
## # A tibble: 10 x 2
## from to
## <chr> <chr>
## 1 GL TP53
## 2 GL KEAP1
## 3 TP53 PLXNB2
## 4 TP53 TERT
## 5 PLXNB2 MAP3K1
## 6 KEAP1 MAP3K1
## 7 TERT MAP3K1
## 8 PLXNB2 FANCC
## 9 KEAP1 FANCC
## 10 TERT FANCC
##
## $fit$clones_expansions$CRUK0007
## # A tibble: 3 x 2
## from to
## <chr> <chr>
## 1 GL PIK3CA
## 2 GL EGFR
## 3 GL SGK223
##
## $fit$clones_expansions$CRUK0008
## # A tibble: 10 x 2
## from to
## <chr> <chr>
## 1 GL KEAP1
## 2 GL STK11
## 3 GL PRDM1
## 4 GL U2AF1
## 5 GL MYC
## 6 KEAP1 ARID2
## 7 STK11 ARID2
## 8 PRDM1 ARID2
## 9 U2AF1 ARID2
## 10 MYC ARID2
##
## $fit$clones_expansions$CRUK0009
## # A tibble: 11 x 2
## from to
## <chr> <chr>
## 1 GL TP53
## 2 GL BRAF
## 3 GL KMT2C
## 4 GL MET
## 5 TP53 ARHGAP35
## 6 TP53 NFE2L2
## 7 BRAF TERT
## 8 ARHGAP35 TERT
## 9 KMT2C TERT
## 10 NFE2L2 TERT
## 11 MET TERT
##
## $fit$clones_expansions$CRUK0010
## # A tibble: 3 x 2
## from to
## <chr> <chr>
## 1 GL SETD2
## 2 GL EGFR
## 3 GL TERT
##
## $fit$clones_expansions$CRUK0011
## # A tibble: 2 x 2
## from to
## <chr> <chr>
## 1 GL KRAS
## 2 KRAS FLT4
##
## $fit$clones_expansions$CRUK0012
## # A tibble: 1 x 2
## from to
## <chr> <chr>
## 1 GL EGFR
##
## $fit$clones_expansions$CRUK0013
## # A tibble: 4 x 2
## from to
## <chr> <chr>
## 1 GL STK11
## 2 STK11 NOTCH1
## 3 STK11 KRAS
## 4 STK11 EGFR
##
## $fit$clones_expansions$CRUK0014
## # A tibble: 6 x 2
## from to
## <chr> <chr>
## 1 GL KRAS
## 2 GL TP53
## 3 KRAS TP53
## 4 TP53 KRAS
## 5 KRAS RNF43
## 6 TP53 RNF43
##
## $fit$clones_expansions$CRUK0015
## # A tibble: 6 x 2
## from to
## <chr> <chr>
## 1 GL BAP1
## 2 GL EGFR
## 3 BAP1 TP53
## 4 EGFR TP53
## 5 BAP1 RB1
## 6 EGFR RB1
##
## $fit$clones_expansions$CRUK0016
## # A tibble: 24 x 2
## from to
## <chr> <chr>
## 1 GL CDKN2A
## 2 GL SPEN
## 3 CDKN2A TP53
## 4 TP53 FAT1
## 5 TP53 CBLB
## 6 TP53 TERT
## 7 FAT1 LATS1
## 8 SPEN LATS1
## 9 CBLB LATS1
## 10 TERT LATS1
## # … with 14 more rows
##
## $fit$clones_expansions$CRUK0017
## # A tibble: 8 x 2
## from to
## <chr> <chr>
## 1 GL KEAP1
## 2 GL MYC
## 3 GL TP53
## 4 KEAP1 ARID2
## 5 MYC ARID2
## 6 TP53 ARID1B
## 7 ARID1B KRAS
## 8 ARID2 KRAS
##
## $fit$clones_expansions$CRUK0018
## # A tibble: 4 x 2
## from to
## <chr> <chr>
## 1 GL KRAS
## 2 GL CMTR2
## 3 GL COL5A2
## 4 KRAS MGA
##
## $fit$clones_expansions$CRUK0019
## # A tibble: 1 x 2
## from to
## <chr> <chr>
## 1 GL EGFR
##
## $fit$clones_expansions$CRUK0020
## # A tibble: 22 x 2
## from to
## <chr> <chr>
## 1 GL KEAP1
## 2 GL COL2A1
## 3 GL PRF1
## 4 GL KRAS
## 5 GL TP53
## 6 ARID2 KRAS
## 7 KEAP1 ARID2
## 8 KEAP1 KRAS
## 9 KRAS TP53
## 10 KRAS MGA
## # … with 12 more rows
##
## $fit$clones_expansions$CRUK0021
## # A tibble: 5 x 2
## from to
## <chr> <chr>
## 1 GL CDKN2A
## 2 GL EGFR
## 3 GL CHEK2
## 4 CDKN2A TP53
## 5 EGFR TP53
##
## $fit$clones_expansions$CRUK0022
## # A tibble: 3 x 2
## from to
## <chr> <chr>
## 1 GL EGFR
## 2 EGFR TP53
## 3 TP53 CIC
##
## $fit$clones_expansions$CRUK0023
## # A tibble: 12 x 2
## from to
## <chr> <chr>
## 1 GL WRN
## 2 GL KRAS
## 3 GL CDKN2A
## 4 WRN PTPRC
## 5 KRAS PTPRC
## 6 CDKN2A PTPRC
## 7 WRN KMT2D
## 8 KRAS KMT2D
## 9 CDKN2A KMT2D
## 10 WRN TP53
## 11 KRAS TP53
## 12 CDKN2A TP53
##
## $fit$clones_expansions$CRUK0024
## # A tibble: 7 x 2
## from to
## <chr> <chr>
## 1 GL STK11
## 2 GL POLE
## 3 EGFR TP53
## 4 STK11 EGFR
## 5 TP53 ATM
## 6 POLE ATM
## 7 ATM NCOR1
##
## $fit$clones_expansions$CRUK0025
## # A tibble: 5 x 2
## from to
## <chr> <chr>
## 1 GL KRAS
## 2 GL TP53
## 3 KRAS TP53
## 4 KRAS MGA
## 5 TP53 KRAS
##
## $fit$clones_expansions$CRUK0026
## # A tibble: 4 x 2
## from to
## <chr> <chr>
## 1 GL EGFR
## 2 GL SERPINB13
## 3 EGFR TP53
## 4 EGFR RB1
##
## $fit$clones_expansions$CRUK0027
## # A tibble: 6 x 2
## from to
## <chr> <chr>
## 1 GL KRAS
## 2 GL TP53
## 3 KRAS TP53
## 4 TP53 KRAS
## 5 KRAS PLXNB2
## 6 TP53 PLXNB2
##
## $fit$clones_expansions$CRUK0028
## # A tibble: 2 x 2
## from to
## <chr> <chr>
## 1 GL APC
## 2 GL EGFR
##
## $fit$clones_expansions$CRUK0029
## # A tibble: 4 x 2
## from to
## <chr> <chr>
## 1 GL TP53
## 2 GL MGA
## 3 GL CCND1
## 4 TP53 NRAS
##
## $fit$clones_expansions$CRUK0030
## # A tibble: 8 x 2
## from to
## <chr> <chr>
## 1 GL TSC2
## 2 GL U2AF1
## 3 GL FBXW7
## 4 GL KRAS
## 5 GL TP53
## 6 KRAS TP53
## 7 TP53 KRAS
## 8 TP53 NF1
##
## $fit$clones_expansions$CRUK0031
## # A tibble: 8 x 2
## from to
## <chr> <chr>
## 1 GL KEAP1
## 2 GL CDKN2A
## 3 GL PRF1
## 4 GL FGFR1
## 5 KEAP1 NF1
## 6 CDKN2A NF1
## 7 PRF1 NF1
## 8 FGFR1 NF1
##
## $fit$clones_expansions$CRUK0032
## # A tibble: 9 x 2
## from to
## <chr> <chr>
## 1 GL ATM
## 2 GL RAD21
## 3 GL U2AF1
## 4 GL RNF43
## 5 ATM CCND1
## 6 RAD21 CCND1
## 7 U2AF1 CCND1
## 8 RNF43 CCND1
## 9 CCND1 ARID1B
##
## $fit$clones_expansions$CRUK0033
## # A tibble: 2 x 2
## from to
## <chr> <chr>
## 1 GL KEAP1
## 2 GL CTNNB1
##
## $fit$clones_expansions$CRUK0034
## # A tibble: 5 x 2
## from to
## <chr> <chr>
## 1 GL KRAS
## 2 GL ATM
## 3 KRAS PLXNB2
## 4 ATM MGA
## 5 PLXNB2 MGA
##
## $fit$clones_expansions$CRUK0035
## # A tibble: 3 x 2
## from to
## <chr> <chr>
## 1 GL TP53
## 2 TP53 FAS
## 3 FAS FLT4
##
## $fit$clones_expansions$CRUK0036
## # A tibble: 7 x 2
## from to
## <chr> <chr>
## 1 GL ARHGAP35
## 2 GL KEAP1
## 3 GL PIK3CA
## 4 ARHGAP35 TERT
## 5 KEAP1 KRAS
## 6 PIK3CA TERT
## 7 TERT KRAS
##
## $fit$clones_expansions$CRUK0037
## # A tibble: 3 x 2
## from to
## <chr> <chr>
## 1 GL NCOA6
## 2 GL CREBBP
## 3 GL KRAS
##
## $fit$clones_expansions$CRUK0038
## # A tibble: 2 x 2
## from to
## <chr> <chr>
## 1 GL KRAS
## 2 KRAS KMT2D
##
## $fit$clones_expansions$CRUK0039
## # A tibble: 4 x 2
## from to
## <chr> <chr>
## 1 GL KRAS
## 2 GL CMTR2
## 3 GL NF1
## 4 GL PHOX2B
##
## $fit$clones_expansions$CRUK0040
## # A tibble: 4 x 2
## from to
## <chr> <chr>
## 1 GL KRAS
## 2 GL RAD21
## 3 GL GATA3
## 4 KRAS NCOR1
##
## $fit$clones_expansions$CRUK0041
## # A tibble: 3 x 2
## from to
## <chr> <chr>
## 1 GL BRAF
## 2 GL EGFR
## 3 BRAF TERT
##
## $fit$clones_expansions$CRUK0042
## # A tibble: 1 x 2
## from to
## <chr> <chr>
## 1 GL KRAS
##
## $fit$clones_expansions$CRUK0043
## # A tibble: 1 x 2
## from to
## <chr> <chr>
## 1 GL MET
##
## $fit$clones_expansions$CRUK0044
## # A tibble: 1 x 2
## from to
## <chr> <chr>
## 1 GL KRAS
##
## $fit$clones_expansions$CRUK0045
## # A tibble: 1 x 2
## from to
## <chr> <chr>
## 1 GL BAP1
##
## $fit$clones_expansions$CRUK0046
## # A tibble: 2 x 2
## from to
## <chr> <chr>
## 1 GL KEAP1
## 2 GL APC
##
## $fit$clones_expansions$CRUK0047
## # A tibble: 5 x 2
## from to
## <chr> <chr>
## 1 GL MYC
## 2 GL STK11
## 3 GL APC
## 4 MYC KRAS
## 5 STK11 KRAS
##
## $fit$clones_expansions$CRUK0048
## # A tibble: 8 x 2
## from to
## <chr> <chr>
## 1 GL EGFR
## 2 GL APC
## 3 GL PRDM1
## 4 GL BRAF
## 5 GL MYC
## 6 EGFR TP53
## 7 EGFR ARHGAP35
## 8 TP53 ARHGAP35
##
## $fit$clones_expansions$CRUK0049
## # A tibble: 8 x 2
## from to
## <chr> <chr>
## 1 GL EGFR
## 2 GL COL2A1
## 3 GL KRAS
## 4 GL TP53
## 5 EGFR TP53
## 6 EGFR RB1
## 7 KRAS TP53
## 8 TP53 KRAS
##
## $fit$clones_expansions$CRUK0050
## # A tibble: 4 x 2
## from to
## <chr> <chr>
## 1 GL MYC
## 2 GL STK11
## 3 MYC KRAS
## 4 STK11 KRAS
##
## $fit$clones_expansions$CRUK0051
## # A tibble: 10 x 2
## from to
## <chr> <chr>
## 1 GL EGFR
## 2 GL FBXW7
## 3 GL KRAS
## 4 GL TP53
## 5 EGFR TP53
## 6 KRAS TP53
## 7 TP53 KRAS
## 8 FBXW7 EP300
## 9 KRAS EP300
## 10 TP53 EP300
##
## $fit$clones_expansions$CRUK0052
## # A tibble: 19 x 2
## from to
## <chr> <chr>
## 1 GL KEAP1
## 2 GL NOTCH2
## 3 GL SGK223
## 4 GL KRAS
## 5 GL TP53
## 6 KEAP1 KRAS
## 7 KEAP1 NF1
## 8 KRAS MGA
## 9 KRAS TP53
## 10 KRAS KMT2D
## 11 MGA NF1
## 12 TP53 KRAS
## 13 TP53 NF1
## 14 KMT2D UBR5
## 15 NOTCH2 UBR5
## 16 NF1 UBR5
## 17 SGK223 UBR5
## 18 KRAS UBR5
## 19 TP53 UBR5
##
## $fit$clones_expansions$CRUK0054
## # A tibble: 1 x 2
## from to
## <chr> <chr>
## 1 GL EGFR
##
## $fit$clones_expansions$CRUK0055
## # A tibble: 4 x 2
## from to
## <chr> <chr>
## 1 GL FANCM
## 2 GL UBR5
## 3 FANCM FAT1
## 4 UBR5 FAT1
##
## $fit$clones_expansions$CRUK0056
## # A tibble: 4 x 2
## from to
## <chr> <chr>
## 1 GL RASA1
## 2 GL CREBBP
## 3 RASA1 TP53
## 4 CREBBP TP53
##
## $fit$clones_expansions$CRUK0057
## # A tibble: 5 x 2
## from to
## <chr> <chr>
## 1 GL TERT
## 2 GL SMARCA4
## 3 GL TSC2
## 4 TERT KRAS
## 5 TERT DNM2
##
## $fit$clones_expansions$CRUK0058
## # A tibble: 2 x 2
## from to
## <chr> <chr>
## 1 GL EGFR
## 2 EGFR TP53
##
## $fit$clones_expansions$CRUK0059
## # A tibble: 1 x 2
## from to
## <chr> <chr>
## 1 GL KRAS
##
## $fit$clones_expansions$CRUK0060
## # A tibble: 12 x 2
## from to
## <chr> <chr>
## 1 GL NCOA6
## 2 GL NF1
## 3 GL SERPINB13
## 4 GL ARID2
## 5 GL PHOX2B
## 6 GL COL2A1
## 7 GL RASA1
## 8 GL NOTCH2
## 9 GL KMT2C
## 10 NCOA6 COL5A2
## 11 NF1 FANCM
## 12 SERPINB13 COL5A2
##
## $fit$clones_expansions$CRUK0061
## # A tibble: 1 x 2
## from to
## <chr> <chr>
## 1 GL STK11
##
## $fit$clones_expansions$CRUK0062
## # A tibble: 13 x 2
## from to
## <chr> <chr>
## 1 GL TP53
## 2 GL PIK3CA
## 3 GL SOX2
## 4 GL CCND1
## 5 TP53 UBR5
## 6 PIK3CA UBR5
## 7 SOX2 UBR5
## 8 CCND1 UBR5
## 9 TP53 FAS
## 10 PIK3CA FAS
## 11 SOX2 FAS
## 12 CCND1 FAS
## 13 UBR5 PLXNB2
##
## $fit$clones_expansions$CRUK0063
## # A tibble: 16 x 2
## from to
## <chr> <chr>
## 1 GL CDKN2A
## 2 GL PIK3CA
## 3 GL SOX2
## 4 GL FBXW7
## 5 GL PRF1
## 6 CDKN2A TP53
## 7 PIK3CA TERT
## 8 SOX2 TERT
## 9 TP53 TERT
## 10 FBXW7 EP300
## 11 TERT EP300
## 12 PRF1 EP300
## 13 EP300 NF1
## 14 EP300 CYLD
## 15 NF1 FANCM
## 16 CYLD FANCM
##
## $fit$clones_expansions$CRUK0064
## # A tibble: 3 x 2
## from to
## <chr> <chr>
## 1 GL TP53
## 2 TP53 MLH1
## 3 TP53 FAT1
##
## $fit$clones_expansions$CRUK0065
## # A tibble: 11 x 2
## from to
## <chr> <chr>
## 1 GL PIK3CA
## 2 GL SOX2
## 3 GL TP53
## 4 PIK3CA NFE2L2
## 5 SOX2 NFE2L2
## 6 TP53 NFE2L2
## 7 NFE2L2 MLH1
## 8 NFE2L2 PTPRC
## 9 NFE2L2 UBR5
## 10 NFE2L2 NOTCH1
## 11 NFE2L2 NCOA6
##
## $fit$clones_expansions$CRUK0066
## # A tibble: 12 x 2
## from to
## <chr> <chr>
## 1 GL CDKN2A
## 2 GL WRN
## 3 GL PDGFRA
## 4 CDKN2A TP53
## 5 TP53 NOTCH1
## 6 TP53 TERT
## 7 TP53 NCOA6
## 8 WRN TP53
## 9 NOTCH1 COL5A2
## 10 PDGFRA COL5A2
## 11 TERT COL5A2
## 12 NCOA6 COL5A2
##
## $fit$clones_expansions$CRUK0067
## # A tibble: 8 x 2
## from to
## <chr> <chr>
## 1 GL CDKN2A
## 2 GL PIK3CA
## 3 GL SOX2
## 4 CDKN2A TP53
## 5 PIK3CA NOTCH1
## 6 SOX2 NOTCH1
## 7 TP53 NOTCH1
## 8 NOTCH1 NFE2L2
##
## $fit$clones_expansions$CRUK0068
## # A tibble: 16 x 2
## from to
## <chr> <chr>
## 1 GL TP53
## 2 GL PTEN
## 3 GL KMT2D
## 4 GL PIK3CA
## 5 GL SOX2
## 6 TP53 SETD2
## 7 PTEN SETD2
## 8 KMT2D SETD2
## 9 PIK3CA SETD2
## 10 SOX2 SETD2
## 11 TP53 TERT
## 12 PTEN TERT
## 13 KMT2D TERT
## 14 PIK3CA TERT
## 15 SOX2 TERT
## 16 SETD2 MGA
##
## $fit$clones_expansions$CRUK0069
## # A tibble: 7 x 2
## from to
## <chr> <chr>
## 1 GL TP53
## 2 GL PDGFRA
## 3 GL FGFR1
## 4 TP53 FAT1
## 5 FAT1 KRAS
## 6 PDGFRA KRAS
## 7 FGFR1 KRAS
##
## $fit$clones_expansions$CRUK0070
## # A tibble: 9 x 2
## from to
## <chr> <chr>
## 1 GL SOX2
## 2 GL TP53
## 3 SOX2 COL5A2
## 4 TP53 DNM2
## 5 TP53 COL5A2
## 6 DNM2 CBLB
## 7 COL5A2 CBLB
## 8 DNM2 NFE2L2
## 9 COL5A2 NFE2L2
##
## $fit$clones_expansions$CRUK0071
## # A tibble: 6 x 2
## from to
## <chr> <chr>
## 1 GL CMTR2
## 2 GL PIK3CA
## 3 GL SOX2
## 4 CMTR2 UBR5
## 5 PIK3CA UBR5
## 6 SOX2 UBR5
##
## $fit$clones_expansions$CRUK0072
## # A tibble: 8 x 2
## from to
## <chr> <chr>
## 1 GL EGFR
## 2 GL PIK3CA
## 3 GL SOX2
## 4 GL MYC
## 5 EGFR TP53
## 6 PIK3CA NFE2L2
## 7 SOX2 NFE2L2
## 8 TP53 NFE2L2
##
## $fit$clones_expansions$CRUK0073
## # A tibble: 15 x 2
## from to
## <chr> <chr>
## 1 GL CDKN2A
## 2 GL FAT1
## 3 GL FGFR1
## 4 GL DICER1
## 5 GL NOTCH2
## 6 GL MYC
## 7 CDKN2A NFE2L2
## 8 CDKN2A KMT2D
## 9 FAT1 NFE2L2
## 10 FGFR1 NFE2L2
## 11 DICER1 PLXNB2
## 12 NFE2L2 PLXNB2
## 13 KMT2D PLXNB2
## 14 NOTCH2 PLXNB2
## 15 MYC PLXNB2
##
## $fit$clones_expansions$CRUK0074
## # A tibble: 9 x 2
## from to
## <chr> <chr>
## 1 GL PIK3CA
## 2 GL SOX2
## 3 GL TP53
## 4 GL CCND1
## 5 PIK3CA NFE2L2
## 6 SOX2 NFE2L2
## 7 TP53 NFE2L2
## 8 NFE2L2 UBR5
## 9 CCND1 UBR5
##
## $fit$clones_expansions$CRUK0075
## # A tibble: 12 x 2
## from to
## <chr> <chr>
## 1 GL PIK3CA
## 2 GL RASA1
## 3 GL MGA
## 4 GL FGFR1
## 5 PIK3CA NOTCH1
## 6 RASA1 TP53
## 7 TP53 NOTCH1
## 8 TP53 FAT1
## 9 NOTCH1 NFE2L2
## 10 FAT1 NFE2L2
## 11 MGA NFE2L2
## 12 FGFR1 NFE2L2
##
## $fit$clones_expansions$CRUK0076
## # A tibble: 12 x 2
## from to
## <chr> <chr>
## 1 GL TP53
## 2 GL SERPINB13
## 3 GL PIK3CA
## 4 GL SOX2
## 5 GL FGFR1
## 6 TP53 ARID1B
## 7 SERPINB13 COL5A2
## 8 ARID1B COL5A2
## 9 PIK3CA COL5A2
## 10 SOX2 COL5A2
## 11 FGFR1 COL5A2
## 12 COL5A2 NCOR1
##
## $fit$clones_expansions$CRUK0077
## # A tibble: 3 x 2
## from to
## <chr> <chr>
## 1 GL TP53
## 2 GL KEAP1
## 3 TP53 LATS1
##
## $fit$clones_expansions$CRUK0078
## # A tibble: 5 x 2
## from to
## <chr> <chr>
## 1 GL FGFR1
## 2 GL PTEN
## 3 GL PIK3CA
## 4 GL SOX2
## 5 FGFR1 PLXNB2
##
## $fit$clones_expansions$CRUK0079
## # A tibble: 6 x 2
## from to
## <chr> <chr>
## 1 GL TP53
## 2 GL POLE
## 3 GL PIK3CA
## 4 GL SOX2
## 5 GL FGFR1
## 6 TP53 FAT1
##
## $fit$clones_expansions$CRUK0080
## # A tibble: 7 x 2
## from to
## <chr> <chr>
## 1 GL EGFR
## 2 GL WT1
## 3 GL CCND1
## 4 EGFR TP53
## 5 TP53 IKZF1
## 6 WT1 IKZF1
## 7 CCND1 IKZF1
##
## $fit$clones_expansions$CRUK0081
## # A tibble: 8 x 2
## from to
## <chr> <chr>
## 1 GL CDKN2A
## 2 CDKN2A TP53
## 3 TP53 NOTCH1
## 4 TP53 FAT1
## 5 TP53 FANCC
## 6 NOTCH1 CYLD
## 7 FAT1 CYLD
## 8 FANCC CYLD
##
## $fit$clones_expansions$CRUK0082
## # A tibble: 11 x 2
## from to
## <chr> <chr>
## 1 GL FGFR1
## 2 GL PIK3CA
## 3 GL SOX2
## 4 GL TP53
## 5 GL WT1
## 6 GL PTEN
## 7 GL KMT2D
## 8 FGFR1 COL5A2
## 9 PIK3CA COL5A2
## 10 SOX2 COL5A2
## 11 TP53 COL5A2
##
## $fit$clones_expansions$CRUK0083
## # A tibble: 7 x 2
## from to
## <chr> <chr>
## 1 GL RASA1
## 2 GL FBXW7
## 3 GL PIK3CA
## 4 GL SOX2
## 5 GL FGFR1
## 6 GL MYC
## 7 RASA1 TP53
##
## $fit$clones_expansions$CRUK0084
## # A tibble: 1 x 2
## from to
## <chr> <chr>
## 1 GL CREBBP
##
## $fit$clones_expansions$CRUK0085
## # A tibble: 4 x 2
## from to
## <chr> <chr>
## 1 GL CHEK2
## 2 GL CREBBP
## 3 GL LATS1
## 4 GL FANCM
##
## $fit$clones_expansions$CRUK0086
## # A tibble: 3 x 2
## from to
## <chr> <chr>
## 1 GL TP53
## 2 GL ARID2
## 3 TP53 FAT1
##
## $fit$clones_expansions$CRUK0087
## # A tibble: 5 x 2
## from to
## <chr> <chr>
## 1 GL PIK3CA
## 2 GL TP53
## 3 GL ASXL1
## 4 PIK3CA NFE2L2
## 5 TP53 NFE2L2
##
## $fit$clones_expansions$CRUK0088
## # A tibble: 2 x 2
## from to
## <chr> <chr>
## 1 GL CUX1
## 2 GL TP53
##
## $fit$clones_expansions$CRUK0089
## # A tibble: 3 x 2
## from to
## <chr> <chr>
## 1 GL PIK3CA
## 2 GL SMAD4
## 3 GL KEAP1
##
## $fit$clones_expansions$CRUK0090
## # A tibble: 5 x 2
## from to
## <chr> <chr>
## 1 GL CDKN2A
## 2 GL NCOA6
## 3 GL CUX1
## 4 GL COL2A1
## 5 GL NRAS
##
## $fit$clones_expansions$CRUK0091
## # A tibble: 3 x 2
## from to
## <chr> <chr>
## 1 GL CDKN2A
## 2 GL SMARCA4
## 3 CDKN2A TP53
##
## $fit$clones_expansions$CRUK0092
## # A tibble: 5 x 2
## from to
## <chr> <chr>
## 1 GL RASA1
## 2 GL PIK3CA
## 3 RASA1 TP53
## 4 TP53 SMAD4
## 5 TP53 CBLB
##
## $fit$clones_expansions$CRUK0093
## # A tibble: 8 x 2
## from to
## <chr> <chr>
## 1 GL CDKN2A
## 2 GL DICER1
## 3 GL COL2A1
## 4 GL GATA3
## 5 CDKN2A TP53
## 6 CDKN2A COL5A2
## 7 TP53 CIC
## 8 TP53 COL5A2
##
## $fit$clones_expansions$CRUK0094
## # A tibble: 2 x 2
## from to
## <chr> <chr>
## 1 GL SMARCA4
## 2 GL TERT
##
## $fit$clones_expansions$CRUK0095
## # A tibble: 3 x 2
## from to
## <chr> <chr>
## 1 GL RASA1
## 2 RASA1 TP53
## 3 TP53 NF1
##
## $fit$clones_expansions$CRUK0096
## # A tibble: 3 x 2
## from to
## <chr> <chr>
## 1 GL KRAS
## 2 GL SGK223
## 3 GL MAP3K1
##
## $fit$clones_expansions$CRUK0097
## # A tibble: 2 x 2
## from to
## <chr> <chr>
## 1 GL TP53
## 2 GL PTEN
##
## $fit$clones_expansions$CRUK0098
## # A tibble: 4 x 2
## from to
## <chr> <chr>
## 1 GL TP53
## 2 GL PTEN
## 3 TP53 UBR5
## 4 PTEN UBR5
##
## $fit$clones_expansions$CRUK0099
## # A tibble: 3 x 2
## from to
## <chr> <chr>
## 1 GL STK11
## 2 GL KEAP1
## 3 GL TP53
##
## $fit$clones_expansions$CRUK0100
## # A tibble: 7 x 2
## from to
## <chr> <chr>
## 1 GL CDKN2A
## 2 GL PHOX2B
## 3 GL STK11
## 4 GL SPEN
## 5 CDKN2A TP53
## 6 CDKN2A COL5A2
## 7 TP53 COL5A2
##
##
##
## $cluster
## $cluster$distances
## $cluster$distances$matrix
## CRUK0001 CRUK0002 CRUK0003 CRUK0004 CRUK0005 CRUK0006 CRUK0007
## CRUK0001 0 67 90 60 105 110 76
## CRUK0002 0 0 71 54 66 71 57
## CRUK0003 0 0 0 77 109 114 60
## CRUK0004 0 0 0 0 92 97 63
## CRUK0005 0 0 0 0 0 72 95
## CRUK0006 0 0 0 0 0 0 100
## CRUK0007 0 0 0 0 0 0 0
## CRUK0008 0 0 0 0 0 0 0
## CRUK0009 0 0 0 0 0 0 0
## CRUK0010 0 0 0 0 0 0 0
## CRUK0011 0 0 0 0 0 0 0
## CRUK0012 0 0 0 0 0 0 0
## CRUK0013 0 0 0 0 0 0 0
## CRUK0014 0 0 0 0 0 0 0
## CRUK0015 0 0 0 0 0 0 0
## CRUK0016 0 0 0 0 0 0 0
## CRUK0017 0 0 0 0 0 0 0
## CRUK0018 0 0 0 0 0 0 0
## CRUK0019 0 0 0 0 0 0 0
## CRUK0020 0 0 0 0 0 0 0
## CRUK0021 0 0 0 0 0 0 0
## CRUK0022 0 0 0 0 0 0 0
## CRUK0023 0 0 0 0 0 0 0
## CRUK0024 0 0 0 0 0 0 0
## CRUK0025 0 0 0 0 0 0 0
## CRUK0026 0 0 0 0 0 0 0
## CRUK0027 0 0 0 0 0 0 0
## CRUK0028 0 0 0 0 0 0 0
## CRUK0029 0 0 0 0 0 0 0
## CRUK0030 0 0 0 0 0 0 0
## CRUK0031 0 0 0 0 0 0 0
## CRUK0032 0 0 0 0 0 0 0
## CRUK0033 0 0 0 0 0 0 0
## CRUK0034 0 0 0 0 0 0 0
## CRUK0035 0 0 0 0 0 0 0
## CRUK0036 0 0 0 0 0 0 0
## CRUK0037 0 0 0 0 0 0 0
## CRUK0038 0 0 0 0 0 0 0
## CRUK0039 0 0 0 0 0 0 0
## CRUK0040 0 0 0 0 0 0 0
## CRUK0041 0 0 0 0 0 0 0
## CRUK0042 0 0 0 0 0 0 0
## CRUK0043 0 0 0 0 0 0 0
## CRUK0044 0 0 0 0 0 0 0
## CRUK0045 0 0 0 0 0 0 0
## CRUK0046 0 0 0 0 0 0 0
## CRUK0047 0 0 0 0 0 0 0
## CRUK0048 0 0 0 0 0 0 0
## CRUK0049 0 0 0 0 0 0 0
## CRUK0050 0 0 0 0 0 0 0
## CRUK0051 0 0 0 0 0 0 0
## CRUK0052 0 0 0 0 0 0 0
## CRUK0054 0 0 0 0 0 0 0
## CRUK0055 0 0 0 0 0 0 0
## CRUK0056 0 0 0 0 0 0 0
## CRUK0057 0 0 0 0 0 0 0
## CRUK0058 0 0 0 0 0 0 0
## CRUK0059 0 0 0 0 0 0 0
## CRUK0060 0 0 0 0 0 0 0
## CRUK0061 0 0 0 0 0 0 0
## CRUK0062 0 0 0 0 0 0 0
## CRUK0063 0 0 0 0 0 0 0
## CRUK0064 0 0 0 0 0 0 0
## CRUK0065 0 0 0 0 0 0 0
## CRUK0066 0 0 0 0 0 0 0
## CRUK0067 0 0 0 0 0 0 0
## CRUK0068 0 0 0 0 0 0 0
## CRUK0069 0 0 0 0 0 0 0
## CRUK0070 0 0 0 0 0 0 0
## CRUK0071 0 0 0 0 0 0 0
## CRUK0072 0 0 0 0 0 0 0
## CRUK0073 0 0 0 0 0 0 0
## CRUK0074 0 0 0 0 0 0 0
## CRUK0075 0 0 0 0 0 0 0
## CRUK0076 0 0 0 0 0 0 0
## CRUK0077 0 0 0 0 0 0 0
## CRUK0078 0 0 0 0 0 0 0
## CRUK0079 0 0 0 0 0 0 0
## CRUK0080 0 0 0 0 0 0 0
## CRUK0081 0 0 0 0 0 0 0
## CRUK0082 0 0 0 0 0 0 0
## CRUK0083 0 0 0 0 0 0 0
## CRUK0084 0 0 0 0 0 0 0
## CRUK0085 0 0 0 0 0 0 0
## CRUK0086 0 0 0 0 0 0 0
## CRUK0087 0 0 0 0 0 0 0
## CRUK0088 0 0 0 0 0 0 0
## CRUK0089 0 0 0 0 0 0 0
## CRUK0090 0 0 0 0 0 0 0
## CRUK0091 0 0 0 0 0 0 0
## CRUK0092 0 0 0 0 0 0 0
## CRUK0093 0 0 0 0 0 0 0
## CRUK0094 0 0 0 0 0 0 0
## CRUK0095 0 0 0 0 0 0 0
## CRUK0096 0 0 0 0 0 0 0
## CRUK0097 0 0 0 0 0 0 0
## CRUK0098 0 0 0 0 0 0 0
## CRUK0099 0 0 0 0 0 0 0
## CRUK0100 0 0 0 0 0 0 0
## CRUK0008 CRUK0009 CRUK0010 CRUK0011 CRUK0012 CRUK0013 CRUK0014
## CRUK0001 94 107 57 74 53 67 123
## CRUK0002 55 66 38 35 34 28 84
## CRUK0003 98 114 61 78 57 71 127
## CRUK0004 81 97 44 61 40 54 110
## CRUK0005 93 71 76 73 72 66 91
## CRUK0006 86 83 81 78 77 71 96
## CRUK0007 84 100 47 64 43 57 113
## CRUK0008 0 98 65 62 61 47 111
## CRUK0009 0 0 81 78 77 71 96
## CRUK0010 0 0 0 45 24 38 94
## CRUK0011 0 0 0 0 41 35 71
## CRUK0012 0 0 0 0 0 34 90
## CRUK0013 0 0 0 0 0 0 84
## CRUK0014 0 0 0 0 0 0 0
## CRUK0015 0 0 0 0 0 0 0
## CRUK0016 0 0 0 0 0 0 0
## CRUK0017 0 0 0 0 0 0 0
## CRUK0018 0 0 0 0 0 0 0
## CRUK0019 0 0 0 0 0 0 0
## CRUK0020 0 0 0 0 0 0 0
## CRUK0021 0 0 0 0 0 0 0
## CRUK0022 0 0 0 0 0 0 0
## CRUK0023 0 0 0 0 0 0 0
## CRUK0024 0 0 0 0 0 0 0
## CRUK0025 0 0 0 0 0 0 0
## CRUK0026 0 0 0 0 0 0 0
## CRUK0027 0 0 0 0 0 0 0
## CRUK0028 0 0 0 0 0 0 0
## CRUK0029 0 0 0 0 0 0 0
## CRUK0030 0 0 0 0 0 0 0
## CRUK0031 0 0 0 0 0 0 0
## CRUK0032 0 0 0 0 0 0 0
## CRUK0033 0 0 0 0 0 0 0
## CRUK0034 0 0 0 0 0 0 0
## CRUK0035 0 0 0 0 0 0 0
## CRUK0036 0 0 0 0 0 0 0
## CRUK0037 0 0 0 0 0 0 0
## CRUK0038 0 0 0 0 0 0 0
## CRUK0039 0 0 0 0 0 0 0
## CRUK0040 0 0 0 0 0 0 0
## CRUK0041 0 0 0 0 0 0 0
## CRUK0042 0 0 0 0 0 0 0
## CRUK0043 0 0 0 0 0 0 0
## CRUK0044 0 0 0 0 0 0 0
## CRUK0045 0 0 0 0 0 0 0
## CRUK0046 0 0 0 0 0 0 0
## CRUK0047 0 0 0 0 0 0 0
## CRUK0048 0 0 0 0 0 0 0
## CRUK0049 0 0 0 0 0 0 0
## CRUK0050 0 0 0 0 0 0 0
## CRUK0051 0 0 0 0 0 0 0
## CRUK0052 0 0 0 0 0 0 0
## CRUK0054 0 0 0 0 0 0 0
## CRUK0055 0 0 0 0 0 0 0
## CRUK0056 0 0 0 0 0 0 0
## CRUK0057 0 0 0 0 0 0 0
## CRUK0058 0 0 0 0 0 0 0
## CRUK0059 0 0 0 0 0 0 0
## CRUK0060 0 0 0 0 0 0 0
## CRUK0061 0 0 0 0 0 0 0
## CRUK0062 0 0 0 0 0 0 0
## CRUK0063 0 0 0 0 0 0 0
## CRUK0064 0 0 0 0 0 0 0
## CRUK0065 0 0 0 0 0 0 0
## CRUK0066 0 0 0 0 0 0 0
## CRUK0067 0 0 0 0 0 0 0
## CRUK0068 0 0 0 0 0 0 0
## CRUK0069 0 0 0 0 0 0 0
## CRUK0070 0 0 0 0 0 0 0
## CRUK0071 0 0 0 0 0 0 0
## CRUK0072 0 0 0 0 0 0 0
## CRUK0073 0 0 0 0 0 0 0
## CRUK0074 0 0 0 0 0 0 0
## CRUK0075 0 0 0 0 0 0 0
## CRUK0076 0 0 0 0 0 0 0
## CRUK0077 0 0 0 0 0 0 0
## CRUK0078 0 0 0 0 0 0 0
## CRUK0079 0 0 0 0 0 0 0
## CRUK0080 0 0 0 0 0 0 0
## CRUK0081 0 0 0 0 0 0 0
## CRUK0082 0 0 0 0 0 0 0
## CRUK0083 0 0 0 0 0 0 0
## CRUK0084 0 0 0 0 0 0 0
## CRUK0085 0 0 0 0 0 0 0
## CRUK0086 0 0 0 0 0 0 0
## CRUK0087 0 0 0 0 0 0 0
## CRUK0088 0 0 0 0 0 0 0
## CRUK0089 0 0 0 0 0 0 0
## CRUK0090 0 0 0 0 0 0 0
## CRUK0091 0 0 0 0 0 0 0
## CRUK0092 0 0 0 0 0 0 0
## CRUK0093 0 0 0 0 0 0 0
## CRUK0094 0 0 0 0 0 0 0
## CRUK0095 0 0 0 0 0 0 0
## CRUK0096 0 0 0 0 0 0 0
## CRUK0097 0 0 0 0 0 0 0
## CRUK0098 0 0 0 0 0 0 0
## CRUK0099 0 0 0 0 0 0 0
## CRUK0100 0 0 0 0 0 0 0
## CRUK0015 CRUK0016 CRUK0017 CRUK0018 CRUK0019 CRUK0020 CRUK0021
## CRUK0001 60 113 114 82 53 165 79
## CRUK0002 54 74 75 43 34 126 73
## CRUK0003 77 103 118 86 57 169 82
## CRUK0004 47 100 101 69 40 152 66
## CRUK0005 92 106 82 77 72 133 111
## CRUK0006 97 111 75 86 77 126 116
## CRUK0007 63 103 104 72 43 155 82
## CRUK0008 81 101 77 70 61 138 100
## CRUK0009 97 117 87 86 77 138 116
## CRUK0010 44 84 85 53 24 136 63
## CRUK0011 61 81 82 30 41 113 80
## CRUK0012 40 80 81 49 20 132 59
## CRUK0013 54 74 75 43 34 126 73
## CRUK0014 110 130 100 79 90 114 129
## CRUK0015 0 100 101 69 40 152 66
## CRUK0016 0 0 121 89 80 172 95
## CRUK0017 0 0 0 90 81 125 120
## CRUK0018 0 0 0 0 49 117 88
## CRUK0019 0 0 0 0 0 132 59
## CRUK0020 0 0 0 0 0 0 171
## CRUK0021 0 0 0 0 0 0 0
## CRUK0022 0 0 0 0 0 0 0
## CRUK0023 0 0 0 0 0 0 0
## CRUK0024 0 0 0 0 0 0 0
## CRUK0025 0 0 0 0 0 0 0
## CRUK0026 0 0 0 0 0 0 0
## CRUK0027 0 0 0 0 0 0 0
## CRUK0028 0 0 0 0 0 0 0
## CRUK0029 0 0 0 0 0 0 0
## CRUK0030 0 0 0 0 0 0 0
## CRUK0031 0 0 0 0 0 0 0
## CRUK0032 0 0 0 0 0 0 0
## CRUK0033 0 0 0 0 0 0 0
## CRUK0034 0 0 0 0 0 0 0
## CRUK0035 0 0 0 0 0 0 0
## CRUK0036 0 0 0 0 0 0 0
## CRUK0037 0 0 0 0 0 0 0
## CRUK0038 0 0 0 0 0 0 0
## CRUK0039 0 0 0 0 0 0 0
## CRUK0040 0 0 0 0 0 0 0
## CRUK0041 0 0 0 0 0 0 0
## CRUK0042 0 0 0 0 0 0 0
## CRUK0043 0 0 0 0 0 0 0
## CRUK0044 0 0 0 0 0 0 0
## CRUK0045 0 0 0 0 0 0 0
## CRUK0046 0 0 0 0 0 0 0
## CRUK0047 0 0 0 0 0 0 0
## CRUK0048 0 0 0 0 0 0 0
## CRUK0049 0 0 0 0 0 0 0
## CRUK0050 0 0 0 0 0 0 0
## CRUK0051 0 0 0 0 0 0 0
## CRUK0052 0 0 0 0 0 0 0
## CRUK0054 0 0 0 0 0 0 0
## CRUK0055 0 0 0 0 0 0 0
## CRUK0056 0 0 0 0 0 0 0
## CRUK0057 0 0 0 0 0 0 0
## CRUK0058 0 0 0 0 0 0 0
## CRUK0059 0 0 0 0 0 0 0
## CRUK0060 0 0 0 0 0 0 0
## CRUK0061 0 0 0 0 0 0 0
## CRUK0062 0 0 0 0 0 0 0
## CRUK0063 0 0 0 0 0 0 0
## CRUK0064 0 0 0 0 0 0 0
## CRUK0065 0 0 0 0 0 0 0
## CRUK0066 0 0 0 0 0 0 0
## CRUK0067 0 0 0 0 0 0 0
## CRUK0068 0 0 0 0 0 0 0
## CRUK0069 0 0 0 0 0 0 0
## CRUK0070 0 0 0 0 0 0 0
## CRUK0071 0 0 0 0 0 0 0
## CRUK0072 0 0 0 0 0 0 0
## CRUK0073 0 0 0 0 0 0 0
## CRUK0074 0 0 0 0 0 0 0
## CRUK0075 0 0 0 0 0 0 0
## CRUK0076 0 0 0 0 0 0 0
## CRUK0077 0 0 0 0 0 0 0
## CRUK0078 0 0 0 0 0 0 0
## CRUK0079 0 0 0 0 0 0 0
## CRUK0080 0 0 0 0 0 0 0
## CRUK0081 0 0 0 0 0 0 0
## CRUK0082 0 0 0 0 0 0 0
## CRUK0083 0 0 0 0 0 0 0
## CRUK0084 0 0 0 0 0 0 0
## CRUK0085 0 0 0 0 0 0 0
## CRUK0086 0 0 0 0 0 0 0
## CRUK0087 0 0 0 0 0 0 0
## CRUK0088 0 0 0 0 0 0 0
## CRUK0089 0 0 0 0 0 0 0
## CRUK0090 0 0 0 0 0 0 0
## CRUK0091 0 0 0 0 0 0 0
## CRUK0092 0 0 0 0 0 0 0
## CRUK0093 0 0 0 0 0 0 0
## CRUK0094 0 0 0 0 0 0 0
## CRUK0095 0 0 0 0 0 0 0
## CRUK0096 0 0 0 0 0 0 0
## CRUK0097 0 0 0 0 0 0 0
## CRUK0098 0 0 0 0 0 0 0
## CRUK0099 0 0 0 0 0 0 0
## CRUK0100 0 0 0 0 0 0 0
## CRUK0022 CRUK0023 CRUK0024 CRUK0025 CRUK0026 CRUK0027 CRUK0028
## CRUK0001 55 115 68 125 59 125 57
## CRUK0002 49 82 42 86 53 86 38
## CRUK0003 72 111 85 129 76 129 61
## CRUK0004 42 108 55 112 46 112 44
## CRUK0005 87 120 80 93 91 93 76
## CRUK0006 92 125 85 98 96 96 81
## CRUK0007 58 111 71 115 62 115 47
## CRUK0008 76 109 61 113 80 113 65
## CRUK0009 92 125 85 98 96 98 81
## CRUK0010 39 92 52 96 43 96 28
## CRUK0011 56 69 49 73 60 73 45
## CRUK0012 35 88 48 92 39 92 24
## CRUK0013 49 82 32 86 53 86 38
## CRUK0014 105 109 98 74 109 74 94
## CRUK0015 42 108 55 112 43 112 44
## CRUK0016 95 104 88 132 99 132 84
## CRUK0017 96 129 89 102 100 102 85
## CRUK0018 64 77 57 77 68 81 53
## CRUK0019 35 88 48 92 39 92 24
## CRUK0020 147 151 140 112 151 116 136
## CRUK0021 61 103 74 131 65 131 63
## CRUK0022 0 103 50 107 41 107 39
## CRUK0023 0 0 96 111 107 111 92
## CRUK0024 0 0 0 100 54 100 52
## CRUK0025 0 0 0 0 111 76 96
## CRUK0026 0 0 0 0 0 111 43
## CRUK0027 0 0 0 0 0 0 96
## CRUK0028 0 0 0 0 0 0 0
## CRUK0029 0 0 0 0 0 0 0
## CRUK0030 0 0 0 0 0 0 0
## CRUK0031 0 0 0 0 0 0 0
## CRUK0032 0 0 0 0 0 0 0
## CRUK0033 0 0 0 0 0 0 0
## CRUK0034 0 0 0 0 0 0 0
## CRUK0035 0 0 0 0 0 0 0
## CRUK0036 0 0 0 0 0 0 0
## CRUK0037 0 0 0 0 0 0 0
## CRUK0038 0 0 0 0 0 0 0
## CRUK0039 0 0 0 0 0 0 0
## CRUK0040 0 0 0 0 0 0 0
## CRUK0041 0 0 0 0 0 0 0
## CRUK0042 0 0 0 0 0 0 0
## CRUK0043 0 0 0 0 0 0 0
## CRUK0044 0 0 0 0 0 0 0
## CRUK0045 0 0 0 0 0 0 0
## CRUK0046 0 0 0 0 0 0 0
## CRUK0047 0 0 0 0 0 0 0
## CRUK0048 0 0 0 0 0 0 0
## CRUK0049 0 0 0 0 0 0 0
## CRUK0050 0 0 0 0 0 0 0
## CRUK0051 0 0 0 0 0 0 0
## CRUK0052 0 0 0 0 0 0 0
## CRUK0054 0 0 0 0 0 0 0
## CRUK0055 0 0 0 0 0 0 0
## CRUK0056 0 0 0 0 0 0 0
## CRUK0057 0 0 0 0 0 0 0
## CRUK0058 0 0 0 0 0 0 0
## CRUK0059 0 0 0 0 0 0 0
## CRUK0060 0 0 0 0 0 0 0
## CRUK0061 0 0 0 0 0 0 0
## CRUK0062 0 0 0 0 0 0 0
## CRUK0063 0 0 0 0 0 0 0
## CRUK0064 0 0 0 0 0 0 0
## CRUK0065 0 0 0 0 0 0 0
## CRUK0066 0 0 0 0 0 0 0
## CRUK0067 0 0 0 0 0 0 0
## CRUK0068 0 0 0 0 0 0 0
## CRUK0069 0 0 0 0 0 0 0
## CRUK0070 0 0 0 0 0 0 0
## CRUK0071 0 0 0 0 0 0 0
## CRUK0072 0 0 0 0 0 0 0
## CRUK0073 0 0 0 0 0 0 0
## CRUK0074 0 0 0 0 0 0 0
## CRUK0075 0 0 0 0 0 0 0
## CRUK0076 0 0 0 0 0 0 0
## CRUK0077 0 0 0 0 0 0 0
## CRUK0078 0 0 0 0 0 0 0
## CRUK0079 0 0 0 0 0 0 0
## CRUK0080 0 0 0 0 0 0 0
## CRUK0081 0 0 0 0 0 0 0
## CRUK0082 0 0 0 0 0 0 0
## CRUK0083 0 0 0 0 0 0 0
## CRUK0084 0 0 0 0 0 0 0
## CRUK0085 0 0 0 0 0 0 0
## CRUK0086 0 0 0 0 0 0 0
## CRUK0087 0 0 0 0 0 0 0
## CRUK0088 0 0 0 0 0 0 0
## CRUK0089 0 0 0 0 0 0 0
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##
## $cluster$distances$dist_obj
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## CRUK0098 73 60 75 48 90 127 48
## CRUK0099 84 71 86 51 104 138 59
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## CRUK0100 126 68 87 134 95 96 86
## CRUK0072 CRUK0073 CRUK0074 CRUK0075 CRUK0076 CRUK0077 CRUK0078
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## CRUK0008 120 82 126 105 131 73 90
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## CRUK0010 91 73 109 88 114 68 73
## CRUK0011 108 70 106 85 111 65 70
## CRUK0012 87 69 105 84 110 64 69
## CRUK0013 101 63 99 78 104 58 63
## CRUK0014 157 119 124 134 129 83 119
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## CRUK0039 116 78 114 93 119 73 78
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## CRUK0060 122 81 120 93 120 79 84
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## CRUK0100 130 78 128 107 133 87 92
## CRUK0079 CRUK0080 CRUK0081 CRUK0082 CRUK0083 CRUK0084 CRUK0085
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## CRUK0080 125 82 134 108 46 51
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## CRUK0093 124 83 57 131 107 45 50
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## CRUK0100 126 85 59 133 109 47 52
## CRUK0086 CRUK0087 CRUK0088 CRUK0089 CRUK0090 CRUK0091 CRUK0092
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## CRUK0051 118 139 111 142 134 136 144
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## CRUK0070 66 87 59 90 82 84 92
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## CRUK0090 65 86 56 58 38 60
## CRUK0091 67 88 60 60 38 62
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## CRUK0096 64 85 57 57 49 51 59
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## CRUK0099 60 81 53 72 76 78 86
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## CRUK0093 CRUK0094 CRUK0095 CRUK0096 CRUK0097 CRUK0098 CRUK0099
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## CRUK0011 62 27 36 25 57 61 72
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## CRUK0036 85 50 59 68 80 84 83
## CRUK0037 68 33 42 31 63 67 78
## CRUK0038 64 29 38 27 59 63 74
## CRUK0039 70 35 44 33 65 69 80
## CRUK0040 65 32 41 30 62 66 77
## CRUK0041 68 33 42 51 63 67 78
## CRUK0042 61 26 35 24 56 60 71
## CRUK0043 44 9 18 27 39 43 54
## CRUK0044 61 26 35 24 56 60 71
## CRUK0045 43 8 17 26 38 42 53
## CRUK0046 57 22 31 40 52 56 55
## CRUK0047 66 31 40 49 61 65 68
## CRUK0048 96 61 70 79 91 95 106
## CRUK0049 145 115 124 113 114 118 129
## CRUK0050 62 27 36 45 57 61 64
## CRUK0051 150 115 124 113 114 118 129
## CRUK0052 153 118 123 113 117 118 120
## CRUK0054 61 26 35 44 56 60 71
## CRUK0055 46 11 20 29 41 45 56
## CRUK0056 57 22 20 40 52 56 67
## CRUK0057 54 13 28 37 49 53 64
## CRUK0058 74 39 48 57 69 73 84
## CRUK0059 61 26 35 24 56 60 71
## CRUK0060 71 41 44 59 71 75 86
## CRUK0061 49 14 23 32 44 48 51
## CRUK0062 125 90 99 108 89 90 104
## CRUK0063 104 93 102 111 123 127 138
## CRUK0064 80 45 54 63 44 48 59
## CRUK0065 124 89 98 107 88 92 103
## CRUK0066 66 55 64 73 85 89 100
## CRUK0067 85 74 83 92 104 108 119
## CRUK0068 132 97 106 115 91 95 111
## CRUK0069 93 58 67 76 57 61 72
## CRUK0070 94 63 72 81 62 66 77
## CRUK0071 84 49 58 67 79 83 94
## CRUK0072 128 93 102 111 123 127 138
## CRUK0073 74 55 64 73 85 89 100
## CRUK0074 126 91 100 109 90 94 105
## CRUK0075 105 70 68 88 100 104 115
## CRUK0076 131 96 105 114 95 99 110
## CRUK0077 85 50 59 68 49 53 52
## CRUK0078 90 55 64 73 80 84 100
## CRUK0079 124 89 98 107 88 92 103
## CRUK0080 83 48 57 66 78 82 93
## CRUK0081 57 46 55 64 76 80 91
## CRUK0082 131 100 109 118 94 98 114
## CRUK0083 107 72 70 90 102 106 117
## CRUK0084 45 10 19 28 40 44 55
## CRUK0085 50 15 24 33 45 49 60
## CRUK0086 81 46 55 64 45 49 60
## CRUK0087 102 67 76 85 66 70 81
## CRUK0088 74 39 48 57 38 42 53
## CRUK0089 74 39 48 57 69 73 72
## CRUK0090 47 31 40 49 61 65 76
## CRUK0091 44 30 42 51 63 67 78
## CRUK0092 76 41 39 59 71 75 86
## CRUK0093 47 56 65 77 81 92
## CRUK0094 47 21 30 42 46 57
## CRUK0095 56 21 39 51 55 66
## CRUK0096 65 30 39 60 64 75
## CRUK0097 77 42 51 60 40 56
## CRUK0098 81 46 55 64 40 60
## CRUK0099 92 57 66 75 56 60
## CRUK0100 54 49 58 67 79 83 86
## CRUK0100
## CRUK0001 96
## CRUK0002 57
## CRUK0003 86
## CRUK0004 83
## CRUK0005 95
## CRUK0006 100
## CRUK0007 86
## CRUK0008 76
## CRUK0009 100
## CRUK0010 67
## CRUK0011 64
## CRUK0012 63
## CRUK0013 49
## CRUK0014 113
## CRUK0015 83
## CRUK0016 77
## CRUK0017 104
## CRUK0018 72
## CRUK0019 63
## CRUK0020 155
## CRUK0021 78
## CRUK0022 78
## CRUK0023 87
## CRUK0024 63
## CRUK0025 115
## CRUK0026 82
## CRUK0027 115
## CRUK0028 67
## CRUK0029 82
## CRUK0030 124
## CRUK0031 72
## CRUK0032 56
## CRUK0033 56
## CRUK0034 69
## CRUK0035 77
## CRUK0036 87
## CRUK0037 70
## CRUK0038 66
## CRUK0039 69
## CRUK0040 69
## CRUK0041 70
## CRUK0042 63
## CRUK0043 46
## CRUK0044 63
## CRUK0045 45
## CRUK0046 59
## CRUK0047 60
## CRUK0048 98
## CRUK0049 152
## CRUK0050 56
## CRUK0051 152
## CRUK0052 155
## CRUK0054 63
## CRUK0055 48
## CRUK0056 59
## CRUK0057 56
## CRUK0058 76
## CRUK0059 63
## CRUK0060 75
## CRUK0061 43
## CRUK0062 127
## CRUK0063 106
## CRUK0064 82
## CRUK0065 126
## CRUK0066 68
## CRUK0067 87
## CRUK0068 134
## CRUK0069 95
## CRUK0070 96
## CRUK0071 86
## CRUK0072 130
## CRUK0073 78
## CRUK0074 128
## CRUK0075 107
## CRUK0076 133
## CRUK0077 87
## CRUK0078 92
## CRUK0079 126
## CRUK0080 85
## CRUK0081 59
## CRUK0082 133
## CRUK0083 109
## CRUK0084 47
## CRUK0085 52
## CRUK0086 83
## CRUK0087 104
## CRUK0088 76
## CRUK0089 76
## CRUK0090 54
## CRUK0091 46
## CRUK0092 78
## CRUK0093 54
## CRUK0094 49
## CRUK0095 58
## CRUK0096 67
## CRUK0097 79
## CRUK0098 83
## CRUK0099 86
## CRUK0100
##
##
## $cluster$parameters
## $cluster$parameters$hc.method
## [1] "ward"
##
## $cluster$parameters$split.method
## [1] "cutreeHybrid"
##
## $cluster$parameters$min.group.size
## [1] 2
##
##
## $cluster$fits
## $cluster$fits$hc
## Call: cluster::agnes(x = cluster$distances$dist_obj, method = hc.method)
## Agglomerative coefficient: 0.8491595
## Order of objects:
## [1] CRUK0001 CRUK0004 CRUK0015 CRUK0022 CRUK0058 CRUK0026 CRUK0080
## [8] CRUK0048 CRUK0021 CRUK0003 CRUK0007 CRUK0010 CRUK0012 CRUK0019
## [15] CRUK0054 CRUK0028 CRUK0041 CRUK0072 CRUK0002 CRUK0032 CRUK0043
## [22] CRUK0045 CRUK0084 CRUK0055 CRUK0094 CRUK0085 CRUK0057 CRUK0056
## [29] CRUK0095 CRUK0033 CRUK0046 CRUK0013 CRUK0061 CRUK0050 CRUK0047
## [36] CRUK0024 CRUK0060 CRUK0008 CRUK0031 CRUK0073 CRUK0016 CRUK0066
## [43] CRUK0081 CRUK0090 CRUK0091 CRUK0093 CRUK0100 CRUK0011 CRUK0042
## [50] CRUK0044 CRUK0059 CRUK0038 CRUK0096 CRUK0040 CRUK0034 CRUK0037
## [57] CRUK0018 CRUK0039 CRUK0023 CRUK0036 CRUK0089 CRUK0092 CRUK0071
## [64] CRUK0078 CRUK0083 CRUK0075 CRUK0063 CRUK0067 CRUK0005 CRUK0029
## [71] CRUK0035 CRUK0088 CRUK0097 CRUK0098 CRUK0064 CRUK0086 CRUK0069
## [78] CRUK0009 CRUK0070 CRUK0006 CRUK0077 CRUK0099 CRUK0017 CRUK0062
## [85] CRUK0065 CRUK0087 CRUK0074 CRUK0068 CRUK0076 CRUK0079 CRUK0082
## [92] CRUK0014 CRUK0027 CRUK0025 CRUK0030 CRUK0052 CRUK0020 CRUK0049
## [99] CRUK0051
## Height (summary):
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 5.00 31.95 56.07 68.11 87.69 352.24
##
## Available components:
## [1] "order" "height" "ac" "merge" "diss" "call"
## [7] "method" "order.lab"
##
## $cluster$fits$dendrogram
## 'dendrogram' with 2 branches and 99 members total, at height 352.2393
##
## $cluster$fits$K
## [1] 11
##
## $cluster$fits$labels
## CRUK0001 CRUK0004 CRUK0015 CRUK0022 CRUK0058 CRUK0026 CRUK0080 CRUK0048
## "C2" "C2" "C2" "C2" "C2" "C2" "C2" "C2"
## CRUK0021 CRUK0003 CRUK0007 CRUK0010 CRUK0012 CRUK0019 CRUK0054 CRUK0028
## "C2" "C2" "C2" "C2" "C2" "C2" "C2" "C2"
## CRUK0041 CRUK0072 CRUK0002 CRUK0032 CRUK0043 CRUK0045 CRUK0084 CRUK0055
## "C2" "C2" "C1" "C1" "C1" "C1" "C1" "C1"
## CRUK0094 CRUK0085 CRUK0057 CRUK0056 CRUK0095 CRUK0033 CRUK0046 CRUK0013
## "C1" "C1" "C1" "C1" "C1" "C1" "C1" "C1"
## CRUK0061 CRUK0050 CRUK0047 CRUK0024 CRUK0060 CRUK0008 CRUK0031 CRUK0073
## "C1" "C1" "C1" "C1" "C1" "C1" "C1" "C1"
## CRUK0016 CRUK0066 CRUK0081 CRUK0090 CRUK0091 CRUK0093 CRUK0100 CRUK0011
## "C5" "C5" "C5" "C5" "C5" "C5" "C5" "C4"
## CRUK0042 CRUK0044 CRUK0059 CRUK0038 CRUK0096 CRUK0040 CRUK0034 CRUK0037
## "C4" "C4" "C4" "C4" "C4" "C4" "C4" "C4"
## CRUK0018 CRUK0039 CRUK0023 CRUK0036 CRUK0089 CRUK0092 CRUK0071 CRUK0078
## "C4" "C4" "C4" "C6" "C6" "C6" "C6" "C6"
## CRUK0083 CRUK0075 CRUK0063 CRUK0067 CRUK0005 CRUK0029 CRUK0035 CRUK0088
## "C6" "C6" "C10" "C10" "C3" "C3" "C3" "C3"
## CRUK0097 CRUK0098 CRUK0064 CRUK0086 CRUK0069 CRUK0009 CRUK0070 CRUK0006
## "C3" "C3" "C3" "C3" "C3" "C3" "C3" "C3"
## CRUK0077 CRUK0099 CRUK0017 CRUK0062 CRUK0065 CRUK0087 CRUK0074 CRUK0068
## "C3" "C3" "C3" "C8" "C8" "C8" "C8" "C8"
## CRUK0076 CRUK0079 CRUK0082 CRUK0014 CRUK0027 CRUK0025 CRUK0030 CRUK0052
## "C9" "C9" "C9" "C7" "C7" "C7" "C7" "C7"
## CRUK0020 CRUK0049 CRUK0051
## "C7" "C11" "C11"
##
##
##
## attr(,"class")
## [1] "rev_cohort_fit"
## attr(,"call")
## revolver_cohort(dataset = subset_data, ONLY.DRIVER = T, MIN.CLUSTER.SIZE = 0)
Access patient-level data
Note Since the new release of REVOLVER, we have implemented the
internal structure of the objects using the tidy data.frame
representations from tidyverse. Most
functions now return tibble data.frames that can be processed with the
dplyr jargon.
Getters
We have made available several types of getters to perform queries on
the data. Getter functions for the data have a common parametrization;
for instance getter functionDrivers takes as input
x a REVOLVER cohort object;patients a list of patients IDs that will be used to subset the
outputs (all by default);
# Access all data for a patient
Data(TRACERx_NEJM_2017_REVOLVER, 'CRUK0001')
## # A tibble: 7 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0001 NF1 TRUE FALSE 1 1
## 2 __mu… CRUK… CRUK0001 ARHGAP35 TRUE FALSE 2 1
## 3 __mu… CRUK… CRUK0001 TP53 TRUE TRUE 3 4
## 4 __mu… CRUK… CRUK0001 MGA TRUE TRUE 3 4
## 5 __mu… CRUK… CRUK0001 WRN TRUE TRUE 3 4
## 6 __mu… Anno… CRUK0001 EGFR TRUE TRUE 3 4
## 7 __mu… CRUK… CRUK0001 PASK TRUE FALSE 5 1
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>
# Access only the drivers for a patient
Drivers(TRACERx_NEJM_2017_REVOLVER, 'CRUK0001')
## # A tibble: 7 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0001 NF1 TRUE FALSE 1 1
## 2 __mu… CRUK… CRUK0001 ARHGAP35 TRUE FALSE 2 1
## 3 __mu… CRUK… CRUK0001 TP53 TRUE TRUE 3 4
## 4 __mu… CRUK… CRUK0001 MGA TRUE TRUE 3 4
## 5 __mu… CRUK… CRUK0001 WRN TRUE TRUE 3 4
## 6 __mu… Anno… CRUK0001 EGFR TRUE TRUE 3 4
## 7 __mu… CRUK… CRUK0001 PASK TRUE FALSE 5 1
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>
# Access the names of the samples for a patient
Samples(TRACERx_NEJM_2017_REVOLVER, 'CRUK0001')
## [1] "R1" "R2" "R3"
# Get the list of truncal (i.e., clonal) mutations in a patient
Truncal(TRACERx_NEJM_2017_REVOLVER, 'CRUK0001')
## # A tibble: 4 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0001 TP53 TRUE TRUE 3 4
## 2 __mu… CRUK… CRUK0001 MGA TRUE TRUE 3 4
## 3 __mu… CRUK… CRUK0001 WRN TRUE TRUE 3 4
## 4 __mu… Anno… CRUK0001 EGFR TRUE TRUE 3 4
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>
# Get the list of subclonal mutations in a patient
Subclonal(TRACERx_NEJM_2017_REVOLVER, 'CRUK0001')
## # A tibble: 3 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0001 NF1 TRUE FALSE 1 1
## 2 __mu… CRUK… CRUK0001 ARHGAP35 TRUE FALSE 2 1
## 3 __mu… CRUK… CRUK0001 PASK TRUE FALSE 5 1
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>
# Return the CCF entry for all the mutations of a patient,
CCF(TRACERx_NEJM_2017_REVOLVER, 'CRUK0001')
## # A tibble: 7 x 8
## id variantID is.driver is.clonal cluster R1 R2 R3
## <chr> <chr> <lgl> <lgl> <chr> <dbl> <dbl> <dbl>
## 1 __mut_id_756 NF1 TRUE FALSE 1 0.86 0 0
## 2 __mut_id_1225 ARHGAP35 TRUE FALSE 2 0.19 0 0.95
## 3 __mut_id_1350 TP53 TRUE TRUE 3 0.99 0.99 1
## 4 __mut_id_1466 MGA TRUE TRUE 3 0.99 0.99 1
## 5 __mut_id_1519 WRN TRUE TRUE 3 0.97 0.98 0.99
## 6 __mut_id_1540 EGFR TRUE TRUE 3 0.99 0.99 1
## 7 __mut_id_1796 PASK TRUE FALSE 5 0.82 0 0.71
# Return the CCF entry for all the clones of a patient, the overall CCF
# values are obtained by REVOLVER from the average of CCF values across clones.
CCF_clusters(TRACERx_NEJM_2017_REVOLVER, 'CRUK0001')
## # A tibble: 4 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 3 4 TRUE TRUE 0.99 0.99 1
## 2 1 1 TRUE FALSE 0.86 0 0
## 3 2 1 TRUE FALSE 0.19 0 0.95
## 4 5 1 TRUE FALSE 0.82 0 0.71
Summary statistics for patients’ data
You can get a broad set of summary statistics about the
TRACERx_NEJM_2017_REVOLVER cohort for a custom set of patients. The
statistics that are available in summarised format are patient-level
(mutatational burdern, drivers etc.), and driver-level (frequency,
clonality
etc.).
# This returns patient-level statistics like the number of biopsies, overall mutations, drivers,
# clones with drivers, truncal and subclonal mutations.
#
# This is also synonim to `Stats(TRACERx_NEJM_2017_REVOLVER)`
Stats_cohort(TRACERx_NEJM_2017_REVOLVER)
## # A tibble: 99 x 7
## patientID numBiopsies numMutations numDriverMutati… numClonesWithDr…
## <chr> <int> <int> <int> <int>
## 1 CRUK0001 3 7 7 4
## 2 CRUK0002 3 7 7 4
## 3 CRUK0003 5 4 4 2
## 4 CRUK0004 4 4 4 2
## 5 CRUK0005 4 6 6 2
## 6 CRUK0006 2 6 6 3
## 7 CRUK0007 2 3 3 1
## 8 CRUK0008 2 6 6 2
## 9 CRUK0009 4 7 7 2
## 10 CRUK0010 2 3 3 1
## # … with 89 more rows, and 2 more variables: numTruncalMutations <int>,
## # numSubclonalMutations <int>
# This returns driver-level statistics like the number of times the driver is clonal,
# subclonal, or found in general, and for quantity normalized by cohort size (i.e., the percentage)
Stats_drivers(TRACERx_NEJM_2017_REVOLVER)
## # A tibble: 79 x 7
## variantID numClonal p_clonal numSubclonal p_subclonal N_tot p_tot
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 TP53 53 0.535 3 0.0303 56 0.566
## 2 KRAS 24 0.242 4 0.0404 28 0.283
## 3 EGFR 21 0.212 1 0.0101 22 0.222
## 4 PIK3CA 20 0.202 1 0.0101 21 0.212
## 5 CDKN2A 14 0.141 0 0 14 0.141
## 6 SOX2 14 0.141 0 0 14 0.141
## 7 KEAP1 12 0.121 0 0 12 0.121
## 8 TERT 11 0.111 2 0.0202 13 0.131
## 9 FGFR1 9 0.0909 0 0 9 0.0909
## 10 STK11 8 0.0808 0 0 8 0.0808
## # … with 69 more rows
The list of all patients in the cohort is accessible as
TRACERx_NEJM_2017_REVOLVER$patients, and these functions can be run on
a smaller subset of
patients.
Stats_cohort(TRACERx_NEJM_2017_REVOLVER, patients = TRACERx_NEJM_2017_REVOLVER$patients[1:5])
## # A tibble: 5 x 7
## patientID numBiopsies numMutations numDriverMutati… numClonesWithDr…
## <chr> <int> <int> <int> <int>
## 1 CRUK0001 3 7 7 4
## 2 CRUK0002 3 7 7 4
## 3 CRUK0003 5 4 4 2
## 4 CRUK0004 4 4 4 2
## 5 CRUK0005 4 6 6 2
## # … with 2 more variables: numTruncalMutations <int>,
## # numSubclonalMutations <int>
Access the trees in the cohort
Trees have getters similar to the data, and getters distinguish from
trees before and after the fit.
Note The tree fits might be slightly different from the trees before
the fit, because their Informatin Transfer is not expanded. Therefore
keep this in mind when comparing trees.
Getters
You can to extract the tree of a patient, before its fit. This can be
one specific tree, or all of them at once. Trees before the fit are
indexed by their rank, which is obtained from the ordering of the tree
scores, which are obtained by the evaluated tree structure before the
fit.
These getters, for instance Phylo, take as parameter
x the cohort object;p the patient identifier;rank the rank of the tree to extract;data to decide whether one wants the trees before the fit
(trees), or the actual fit tree fits.
By logic, if you are asking for the fit trees (data = 'fits'), the
rank parameter is not considered (because there is only 1 tree fit by
REVOLVER).
# Access the top-rank tree for a patient
Phylo(TRACERx_NEJM_2017_REVOLVER, 'CRUK0001', rank = 1)
## [ ctree - ctree rank 1/3 for CRUK0001 ]
##
## # A tibble: 4 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 3 4 TRUE TRUE 0.99 0.99 1
## 2 1 1 TRUE FALSE 0.86 0 0
## 3 2 1 TRUE FALSE 0.19 0 0.95
## 4 5 1 TRUE FALSE 0.82 0 0.71
##
## Tree shape (drivers annotated)
##
## \-GL
## \-3 [R2] :: TP53, MGA, WRN, EGFR
## |-1 :: NF1
## | \-5 :: PASK
## \-2 :: ARHGAP35
##
## Information transfer
##
## GL ---> TP53
## GL ---> MGA
## GL ---> WRN
## GL ---> EGFR
## TP53 ---> NF1
## MGA ---> NF1
## WRN ---> NF1
## EGFR ---> NF1
## TP53 ---> ARHGAP35
## MGA ---> ARHGAP35
## WRN ---> ARHGAP35
## EGFR ---> ARHGAP35
## NF1 ---> PASK
##
## Tree score 0.111111111111111
# Access all trees for a patient. We use CRUK0002 because it has only 3 trees
Phylo(TRACERx_NEJM_2017_REVOLVER, 'CRUK0002', rank = NULL)
## $`1`
## [ ctree - ctree rank 1/2 for CRUK0002 ]
##
## # A tibble: 4 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE FALSE 0 0.92 0
## 2 2 2 TRUE TRUE 0.99 0.98 0.99
## 3 5 1 TRUE FALSE 0.78 0 0
## 4 6 1 TRUE FALSE 0.96 0.03 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-2 :: MET, TERT
## |-6 :: EP300
## | \-5 :: NF1
## \-1 :: RB1, IKZF1, KRAS
##
## Information transfer
##
## MET ---> RB1
## MET ---> IKZF1
## MET ---> KRAS
## TERT ---> RB1
## TERT ---> IKZF1
## TERT ---> KRAS
## GL ---> MET
## GL ---> TERT
## EP300 ---> NF1
## MET ---> EP300
## TERT ---> EP300
##
## Tree score 0.75
##
## $`2`
## [ ctree - ctree rank 2/2 for CRUK0002 ]
##
## # A tibble: 4 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE FALSE 0 0.92 0
## 2 2 2 TRUE TRUE 0.99 0.98 0.99
## 3 5 1 TRUE FALSE 0.78 0 0
## 4 6 1 TRUE FALSE 0.96 0.03 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-2 :: MET, TERT
## \-1 :: RB1, IKZF1, KRAS
## \-6 :: EP300
## \-5 :: NF1
##
## Information transfer
##
## MET ---> RB1
## MET ---> IKZF1
## MET ---> KRAS
## TERT ---> RB1
## TERT ---> IKZF1
## TERT ---> KRAS
## GL ---> MET
## GL ---> TERT
## EP300 ---> NF1
## RB1 ---> EP300
## IKZF1 ---> EP300
## KRAS ---> EP300
##
## Tree score 0.0833333333333333
Notice that in the printing of a tree to screen you can immediately see
the Information Transfer (IT) for the driver genes. In general, you can
access the IT of a tree with another getter, which takes as extra
parameter type in order to return either the transfer across drivers,
or across clones annotated in a tree.
# Information Transfer for the drivers, top-ranking tree
ITransfer(TRACERx_NEJM_2017_REVOLVER, "CRUK0001", rank = 1, type = 'drivers')
## # A tibble: 13 x 2
## from to
## <chr> <chr>
## 1 GL TP53
## 2 GL MGA
## 3 GL WRN
## 4 GL EGFR
## 5 TP53 NF1
## 6 MGA NF1
## 7 WRN NF1
## 8 EGFR NF1
## 9 TP53 ARHGAP35
## 10 MGA ARHGAP35
## 11 WRN ARHGAP35
## 12 EGFR ARHGAP35
## 13 NF1 PASK
# Information Transfer for the clones, top-ranking tree
ITransfer(TRACERx_NEJM_2017_REVOLVER, "CRUK0001", rank = 1, type = 'clones')
## # A tibble: 4 x 2
## from to
## <chr> <chr>
## 1 GL 3
## 2 3 1
## 3 3 2
## 4 1 5
Fit trees can be accessed using the data argument. Essentially this is
like before, but does not require specifying a rank parameter.
# Access the fit tree for a patient
Phylo(TRACERx_NEJM_2017_REVOLVER, 'CRUK0001', data = 'fits')
## [ ctree - ctree rank 1/3 for CRUK0001 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 4 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 3 4 TRUE TRUE 0.99 0.99 1
## 2 1 1 TRUE FALSE 0.86 0 0
## 3 2 1 TRUE FALSE 0.19 0 0.95
## 4 5 1 TRUE FALSE 0.82 0 0.71
##
## Tree shape (drivers annotated)
##
## \-GL
## \-3 [R2] :: TP53, MGA, WRN, EGFR
## |-1 :: NF1
## | \-5 :: PASK
## \-2 :: ARHGAP35
##
## Information transfer
##
## GL ---> EGFR
## GL ---> WRN
## GL ---> MGA
## EGFR ---> TP53
## WRN ---> TP53
## TP53 ---> NF1
## MGA ---> NF1
## TP53 ---> ARHGAP35
## MGA ---> ARHGAP35
## NF1 ---> PASK
##
## Tree score 0.111111111111111
# Information Transfer for the drivers, top-ranking tree. Notice that this is different
# from the result of the above call, because the transfer after fitting is expanded
ITransfer(TRACERx_NEJM_2017_REVOLVER, "CRUK0001", rank = 1, type = 'drivers', data = 'fits')
## # A tibble: 10 x 2
## from to
## <chr> <chr>
## 1 GL EGFR
## 2 GL WRN
## 3 GL MGA
## 4 EGFR TP53
## 5 WRN TP53
## 6 TP53 NF1
## 7 MGA NF1
## 8 TP53 ARHGAP35
## 9 MGA ARHGAP35
## 10 NF1 PASK
Summary statistics for trees and fits
There are getters for summary statistics that work for trees and fits,
with the same principles fo the getters for the data discussed
above
# This returns patient-level statistics for the trees available in a patient. The tibble reports
# whether the patient has trees annotated, the total number of trees, their minimum and maximum
# scores mutations and the total number of differnet combinations of Information Transfer for
# the available trees.
Stats_trees(TRACERx_NEJM_2017_REVOLVER)
## # A tibble: 99 x 6
## patientID hasTrees numTrees maxScore minScore combInfTransf
## <chr> <lgl> <int> <dbl> <dbl> <int>
## 1 CRUK0001 TRUE 3 0.111 0.111 3
## 2 CRUK0002 TRUE 2 0.75 0.0833 2
## 3 CRUK0003 TRUE 1 1 1 1
## 4 CRUK0004 TRUE 1 1 1 1
## 5 CRUK0005 TRUE 1 1 1 1
## 6 CRUK0006 TRUE 2 0.667 0.167 2
## 7 CRUK0007 TRUE 1 1 1 1
## 8 CRUK0008 TRUE 1 1 1 1
## 9 CRUK0009 TRUE 1 1 1 1
## 10 CRUK0010 TRUE 1 1 1 1
## # … with 89 more rows
# This returns the same table of above, but with some extended information on the fits (like the fit rank, etc)
Stats_fits(TRACERx_NEJM_2017_REVOLVER)
## # A tibble: 99 x 9
## patientID hasTrees numTrees maxScore minScore combInfTransf Solution
## <chr> <lgl> <int> <dbl> <dbl> <int> <int>
## 1 CRUK0001 TRUE 3 0.111 0.111 3 1
## 2 CRUK0002 TRUE 2 0.75 0.0833 2 1
## 3 CRUK0003 TRUE 1 1 1 1 1
## 4 CRUK0004 TRUE 1 1 1 1 1
## 5 CRUK0005 TRUE 1 1 1 1 1
## 6 CRUK0006 TRUE 2 0.667 0.167 2 1
## 7 CRUK0007 TRUE 1 1 1 1 1
## 8 CRUK0008 TRUE 1 1 1 1 1
## 9 CRUK0009 TRUE 1 1 1 1 1
## 10 CRUK0010 TRUE 1 1 1 1 1
## # … with 89 more rows, and 2 more variables: converged <lgl>,
## # penalty <dbl>
caravagn/revolver documentation built on May 21, 2022, 5:48 p.m.
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Getter functions
Giulio Caravagna May 1, 2019
# Load REVOLVER
library(revolver)
## [ ctree - Clone Trees in cancer ]
## Author : Giulio Caravagna <gcaravagn@gmail.com>
## GitHub : caravagn/ctree
##
## Available datasets ~ use data('xxx', package='REVOLVER_datasets') to load dataset 'xxx'
##
## ◉ TRACERx_NEJM_2017 Mutations from TRACERx lung (NEJM2017, PMID: 28445112). n = 99 patients, multi-region WES.
## ◉ TRACERx_NEJM_2017_REVOLVER REVOLVER analysis of TRACERx_NEJM_2017.
## [ REVOLVER - Repeated Evolution in Cancer ]
## Author : Giulio Caravagna <gcaravagn@gmail.com>
## GitHub : caravagn/revolver
In this vignette we make use of one of the cohort objects released with the tool.
# Data released in the 'evoverse.datasets'
data('TRACERx_NEJM_2017_REVOLVER', package = 'evoverse.datasets')
# We can use S3 object functions to retrieve simple information about the plot.
# The `print` functions runs also the `revolver_check_cohort` function which
# tells us that some patient have only 1 clone with drivers, and therefore they
# can just be expanded.
TRACERx_NEJM_2017_REVOLVER
## $patients
## [1] "CRUK0001" "CRUK0002" "CRUK0003" "CRUK0004" "CRUK0005" "CRUK0006"
## [7] "CRUK0007" "CRUK0008" "CRUK0009" "CRUK0010" "CRUK0011" "CRUK0012"
## [13] "CRUK0013" "CRUK0014" "CRUK0015" "CRUK0016" "CRUK0017" "CRUK0018"
## [19] "CRUK0019" "CRUK0020" "CRUK0021" "CRUK0022" "CRUK0023" "CRUK0024"
## [25] "CRUK0025" "CRUK0026" "CRUK0027" "CRUK0028" "CRUK0029" "CRUK0030"
## [31] "CRUK0031" "CRUK0032" "CRUK0033" "CRUK0034" "CRUK0035" "CRUK0036"
## [37] "CRUK0037" "CRUK0038" "CRUK0039" "CRUK0040" "CRUK0041" "CRUK0042"
## [43] "CRUK0043" "CRUK0044" "CRUK0045" "CRUK0046" "CRUK0047" "CRUK0048"
## [49] "CRUK0049" "CRUK0050" "CRUK0051" "CRUK0052" "CRUK0054" "CRUK0055"
## [55] "CRUK0056" "CRUK0057" "CRUK0058" "CRUK0059" "CRUK0060" "CRUK0061"
## [61] "CRUK0062" "CRUK0063" "CRUK0064" "CRUK0065" "CRUK0066" "CRUK0067"
## [67] "CRUK0068" "CRUK0069" "CRUK0070" "CRUK0071" "CRUK0072" "CRUK0073"
## [73] "CRUK0074" "CRUK0075" "CRUK0076" "CRUK0077" "CRUK0078" "CRUK0079"
## [79] "CRUK0080" "CRUK0081" "CRUK0082" "CRUK0083" "CRUK0084" "CRUK0085"
## [85] "CRUK0086" "CRUK0087" "CRUK0088" "CRUK0089" "CRUK0090" "CRUK0091"
## [91] "CRUK0092" "CRUK0093" "CRUK0094" "CRUK0095" "CRUK0096" "CRUK0097"
## [97] "CRUK0098" "CRUK0099" "CRUK0100"
##
## $variantIDs
## [1] "NF1" "ARHGAP35" "TP53" "MGA" "WRN"
## [6] "EGFR" "PASK" "RB1" "IKZF1" "KRAS"
## [11] "MET" "TERT" "EP300" "PIK3CA" "CDKN2A"
## [16] "CTNNB1" "SMAD4" "NOTCH1" "NRAS" "CMTR2"
## [21] "BRAF" "PLXNB2" "KEAP1" "MAP3K1" "FANCC"
## [26] "SGK223" "STK11" "PRDM1" "U2AF1" "MYC"
## [31] "ARID2" "KMT2C" "NFE2L2" "SETD2" "FLT4"
## [36] "RNF43" "BAP1" "FAT1" "SPEN" "CBLB"
## [41] "ASXL1" "PTPRC" "DNM2" "LATS1" "ARID1B"
## [46] "COL5A2" "COL2A1" "PRF1" "NCOR1" "CHEK2"
## [51] "CIC" "KMT2D" "POLE" "ATM" "SERPINB13"
## [56] "APC" "CCND1" "TSC2" "FBXW7" "FGFR1"
## [61] "RAD21" "FAS" "NCOA6" "CREBBP" "PHOX2B"
## [66] "GATA3" "NOTCH2" "UBR5" "FANCM" "RASA1"
## [71] "SMARCA4" "SOX2" "CYLD" "MLH1" "PDGFRA"
## [76] "PTEN" "DICER1" "WT1" "CUX1"
##
## $variantIDs.driver
## [1] "NF1" "ARHGAP35" "TP53" "MGA" "WRN"
## [6] "EGFR" "PASK" "RB1" "IKZF1" "KRAS"
## [11] "MET" "TERT" "EP300" "PIK3CA" "CDKN2A"
## [16] "CTNNB1" "SMAD4" "NOTCH1" "NRAS" "CMTR2"
## [21] "BRAF" "PLXNB2" "KEAP1" "MAP3K1" "FANCC"
## [26] "SGK223" "STK11" "PRDM1" "U2AF1" "MYC"
## [31] "ARID2" "KMT2C" "NFE2L2" "SETD2" "FLT4"
## [36] "RNF43" "BAP1" "FAT1" "SPEN" "CBLB"
## [41] "ASXL1" "PTPRC" "DNM2" "LATS1" "ARID1B"
## [46] "COL5A2" "COL2A1" "PRF1" "NCOR1" "CHEK2"
## [51] "CIC" "KMT2D" "POLE" "ATM" "SERPINB13"
## [56] "APC" "CCND1" "TSC2" "FBXW7" "FGFR1"
## [61] "RAD21" "FAS" "NCOA6" "CREBBP" "PHOX2B"
## [66] "GATA3" "NOTCH2" "UBR5" "FANCM" "RASA1"
## [71] "SMARCA4" "SOX2" "CYLD" "MLH1" "PDGFRA"
## [76] "PTEN" "DICER1" "WT1" "CUX1"
##
## $numVariants
## [1] 450
##
## $annotation
## [1] "TRACERx NEJM 2017"
##
## $dataset
## $dataset$CRUK0001
## # A tibble: 7 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0001 NF1 TRUE FALSE 1 1
## 2 __mu… CRUK… CRUK0001 ARHGAP35 TRUE FALSE 2 1
## 3 __mu… CRUK… CRUK0001 TP53 TRUE TRUE 3 4
## 4 __mu… CRUK… CRUK0001 MGA TRUE TRUE 3 4
## 5 __mu… CRUK… CRUK0001 WRN TRUE TRUE 3 4
## 6 __mu… Anno… CRUK0001 EGFR TRUE TRUE 3 4
## 7 __mu… CRUK… CRUK0001 PASK TRUE FALSE 5 1
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>
##
## $dataset$CRUK0002
## # A tibble: 7 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0002 RB1 TRUE FALSE 1 3
## 2 __mu… CRUK… CRUK0002 IKZF1 TRUE FALSE 1 3
## 3 __mu… Anno… CRUK0002 KRAS TRUE FALSE 1 3
## 4 __mu… CRUK… CRUK0002 MET TRUE TRUE 2 2
## 5 __mu… Anno… CRUK0002 TERT TRUE TRUE 2 2
## 6 __mu… CRUK… CRUK0002 NF1 TRUE FALSE 5 1
## 7 __mu… CRUK… CRUK0002 EP300 TRUE FALSE 6 1
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>
##
## $dataset$CRUK0003
## # A tibble: 4 x 14
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0003 PIK3CA TRUE TRUE 1 3
## 2 __mu… CRUK… CRUK0003 EGFR TRUE TRUE 1 3
## 3 __mu… Anno… CRUK0003 CDKN2A TRUE TRUE 1 3
## 4 __mu… CRUK… CRUK0003 CTNNB1 TRUE FALSE 4 1
## # … with 6 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>, R6 <dbl>
##
## $dataset$CRUK0004
## # A tibble: 4 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0004 SMAD4 TRUE FALSE 1 2
## 2 __mu… CRUK… CRUK0004 NOTCH1 TRUE FALSE 1 2
## 3 __mu… CRUK… CRUK0004 TP53 TRUE TRUE 2 2
## 4 __mu… CRUK… CRUK0004 EGFR TRUE TRUE 2 2
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>
##
## $dataset$CRUK0005
## # A tibble: 6 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0005 NRAS TRUE FALSE 1 1
## 2 __mu… CRUK… CRUK0005 CMTR2 TRUE TRUE 2 5
## 3 __mu… CRUK… CRUK0005 TP53 TRUE TRUE 2 5
## 4 __mu… CRUK… CRUK0005 BRAF TRUE TRUE 2 5
## 5 __mu… CRUK… CRUK0005 PASK TRUE TRUE 2 5
## 6 __mu… Anno… CRUK0005 TERT TRUE TRUE 2 5
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>
##
## $dataset$CRUK0006
## # A tibble: 6 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0006 PLXNB2 TRUE TRUE 1 4
## 2 __mu… CRUK… CRUK0006 TP53 TRUE TRUE 1 4
## 3 __mu… CRUK… CRUK0006 KEAP1 TRUE TRUE 1 4
## 4 __mu… Anno… CRUK0006 TERT TRUE TRUE 1 4
## 5 __mu… CRUK… CRUK0006 MAP3K1 TRUE FALSE 2 1
## 6 __mu… CRUK… CRUK0006 FANCC TRUE FALSE 7 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0007
## # A tibble: 3 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0007 PIK3CA TRUE TRUE 1 3
## 2 __mu… CRUK… CRUK0007 EGFR TRUE TRUE 1 3
## 3 __mu… Anno… CRUK0007 SGK223 TRUE TRUE 1 3
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0008
## # A tibble: 6 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0008 KEAP1 TRUE TRUE 2 5
## 2 __mu… CRUK… CRUK0008 STK11 TRUE TRUE 2 5
## 3 __mu… CRUK… CRUK0008 PRDM1 TRUE TRUE 2 5
## 4 __mu… CRUK… CRUK0008 U2AF1 TRUE TRUE 2 5
## 5 __mu… Anno… CRUK0008 MYC TRUE TRUE 2 5
## 6 __mu… CRUK… CRUK0008 ARID2 TRUE FALSE 3 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0009
## # A tibble: 7 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0009 BRAF TRUE TRUE 1 6
## 2 __mu… CRUK… CRUK0009 TP53 TRUE TRUE 1 6
## 3 __mu… CRUK… CRUK0009 ARHGAP35 TRUE TRUE 1 6
## 4 __mu… CRUK… CRUK0009 KMT2C TRUE TRUE 1 6
## 5 __mu… Anno… CRUK0009 NFE2L2 TRUE TRUE 1 6
## 6 __mu… Anno… CRUK0009 MET TRUE TRUE 1 6
## 7 __mu… Anno… CRUK0009 TERT TRUE FALSE 2 1
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>
##
## $dataset$CRUK0010
## # A tibble: 3 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0010 SETD2 TRUE TRUE 1 3
## 2 __mu… CRUK… CRUK0010 EGFR TRUE TRUE 1 3
## 3 __mu… Anno… CRUK0010 TERT TRUE TRUE 1 3
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0011
## # A tibble: 2 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0011 KRAS TRUE TRUE 1 1
## 2 __mu… CRUK… CRUK0011 FLT4 TRUE FALSE 3 1
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>
##
## $dataset$CRUK0012
## # A tibble: 1 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0012 EGFR TRUE TRUE 1 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0013
## # A tibble: 4 x 14
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0013 STK11 TRUE TRUE 1 1
## 2 __mu… CRUK… CRUK0013 NOTCH1 TRUE FALSE 2 1
## 3 __mu… Anno… CRUK0013 KRAS TRUE FALSE 3 1
## 4 __mu… Anno… CRUK0013 EGFR TRUE FALSE 4 1
## # … with 6 more variables: CCF <chr>, LN1 <dbl>, LN2 <dbl>, R1 <dbl>,
## # R2 <dbl>, R3 <dbl>
##
## $dataset$CRUK0014
## # A tibble: 3 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0014 TP53 TRUE TRUE 1 2
## 2 __mu… CRUK… CRUK0014 KRAS TRUE TRUE 1 2
## 3 __mu… CRUK… CRUK0014 RNF43 TRUE FALSE 2 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0015
## # A tibble: 4 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0015 BAP1 TRUE TRUE 1 2
## 2 __mu… CRUK… CRUK0015 EGFR TRUE TRUE 1 2
## 3 __mu… CRUK… CRUK0015 TP53 TRUE FALSE 2 1
## 4 __mu… CRUK… CRUK0015 RB1 TRUE FALSE 3 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0016
## # A tibble: 11 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0016 TP53 TRUE TRUE 1 6
## 2 __mu… CRUK… CRUK0016 FAT1 TRUE TRUE 1 6
## 3 __mu… CRUK… CRUK0016 SPEN TRUE TRUE 1 6
## 4 __mu… CRUK… CRUK0016 CBLB TRUE TRUE 1 6
## 5 __mu… Anno… CRUK0016 TERT TRUE TRUE 1 6
## 6 __mu… Anno… CRUK0016 CDKN2A TRUE TRUE 1 6
## 7 __mu… CRUK… CRUK0016 ASXL1 TRUE FALSE 2 1
## 8 __mu… CRUK… CRUK0016 PTPRC TRUE FALSE 6 1
## 9 __mu… CRUK… CRUK0016 DNM2 TRUE FALSE 10 1
## 10 __mu… CRUK… CRUK0016 LATS1 TRUE FALSE 16 2
## 11 __mu… CRUK… CRUK0016 ARID1B TRUE FALSE 16 2
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0017
## # A tibble: 6 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0017 TP53 TRUE TRUE 1 5
## 2 __mu… CRUK… CRUK0017 ARID1B TRUE TRUE 1 5
## 3 __mu… CRUK… CRUK0017 ARID2 TRUE TRUE 1 5
## 4 __mu… CRUK… CRUK0017 KEAP1 TRUE TRUE 1 5
## 5 __mu… Anno… CRUK0017 MYC TRUE TRUE 1 5
## 6 __mu… CRUK… CRUK0017 KRAS TRUE FALSE 3 1
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>
##
## $dataset$CRUK0018
## # A tibble: 4 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0018 CMTR2 TRUE TRUE 1 4
## 2 __mu… CRUK… CRUK0018 KRAS TRUE TRUE 1 4
## 3 __mu… CRUK… CRUK0018 MGA TRUE TRUE 1 4
## 4 __mu… CRUK… CRUK0018 COL5A2 TRUE TRUE 1 4
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>
##
## $dataset$CRUK0019
## # A tibble: 1 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0019 EGFR TRUE TRUE 1 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0020
## # A tibble: 10 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0020 KEAP1 TRUE TRUE 1 7
## 2 __mu… CRUK… CRUK0020 TP53 TRUE TRUE 1 7
## 3 __mu… CRUK… CRUK0020 MGA TRUE TRUE 1 7
## 4 __mu… CRUK… CRUK0020 ARID2 TRUE TRUE 1 7
## 5 __mu… CRUK… CRUK0020 COL2A1 TRUE TRUE 1 7
## 6 __mu… CRUK… CRUK0020 PRF1 TRUE TRUE 1 7
## 7 __mu… Anno… CRUK0020 KRAS TRUE TRUE 1 7
## 8 __mu… CRUK… CRUK0020 PIK3CA TRUE FALSE 2 1
## 9 __mu… CRUK… CRUK0020 BAP1 TRUE FALSE 3 1
## 10 __mu… CRUK… CRUK0020 NCOR1 TRUE FALSE 4 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0021
## # A tibble: 4 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0021 EGFR TRUE TRUE 1 4
## 2 __mu… CRUK… CRUK0021 TP53 TRUE TRUE 1 4
## 3 __mu… CRUK… CRUK0021 CHEK2 TRUE TRUE 1 4
## 4 __mu… Anno… CRUK0021 CDKN2A TRUE TRUE 1 4
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0022
## # A tibble: 3 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0022 TP53 TRUE TRUE 1 2
## 2 __mu… CRUK… CRUK0022 EGFR TRUE TRUE 1 2
## 3 __mu… CRUK… CRUK0022 CIC TRUE FALSE 2 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0023
## # A tibble: 6 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0023 WRN TRUE TRUE 1 3
## 2 __mu… CRUK… CRUK0023 KRAS TRUE TRUE 1 3
## 3 __mu… Anno… CRUK0023 CDKN2A TRUE TRUE 1 3
## 4 __mu… CRUK… CRUK0023 TP53 TRUE FALSE 2 1
## 5 __mu… CRUK… CRUK0023 PTPRC TRUE FALSE 4 2
## 6 __mu… CRUK… CRUK0023 KMT2D TRUE FALSE 4 2
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>
##
## $dataset$CRUK0024
## # A tibble: 6 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0024 TP53 TRUE TRUE 1 4
## 2 __mu… CRUK… CRUK0024 STK11 TRUE TRUE 1 4
## 3 __mu… CRUK… CRUK0024 POLE TRUE TRUE 1 4
## 4 __mu… Anno… CRUK0024 EGFR TRUE TRUE 1 4
## 5 __mu… CRUK… CRUK0024 ATM TRUE FALSE 3 1
## 6 __mu… CRUK… CRUK0024 NCOR1 TRUE FALSE 4 1
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R3 <dbl>, R4 <dbl>,
## # R6 <dbl>
##
## $dataset$CRUK0025
## # A tibble: 3 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0025 KRAS TRUE TRUE 1 3
## 2 __mu… CRUK… CRUK0025 TP53 TRUE TRUE 1 3
## 3 __mu… CRUK… CRUK0025 MGA TRUE TRUE 1 3
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>
##
## $dataset$CRUK0026
## # A tibble: 4 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0026 TP53 TRUE TRUE 1 4
## 2 __mu… CRUK… CRUK0026 EGFR TRUE TRUE 1 4
## 3 __mu… CRUK… CRUK0026 RB1 TRUE TRUE 1 4
## 4 __mu… CRUK… CRUK0026 SERPINB13 TRUE TRUE 1 4
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0027
## # A tibble: 3 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0027 KRAS TRUE TRUE 1 2
## 2 __mu… CRUK… CRUK0027 TP53 TRUE TRUE 1 2
## 3 __mu… CRUK… CRUK0027 PLXNB2 TRUE FALSE 2 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0028
## # A tibble: 2 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0028 APC TRUE TRUE 1 2
## 2 __mu… Anno… CRUK0028 EGFR TRUE TRUE 1 2
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0029
## # A tibble: 4 x 15
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0029 TP53 TRUE TRUE 1 4
## 2 __mu… CRUK… CRUK0029 NRAS TRUE TRUE 1 4
## 3 __mu… CRUK… CRUK0029 MGA TRUE TRUE 1 4
## 4 __mu… Anno… CRUK0029 CCND1 TRUE TRUE 1 4
## # … with 7 more variables: CCF <chr>, R2 <dbl>, R4 <dbl>, R5 <dbl>,
## # R6 <dbl>, R7 <dbl>, R8 <dbl>
##
## $dataset$CRUK0030
## # A tibble: 6 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0030 KRAS TRUE TRUE 1 6
## 2 __mu… CRUK… CRUK0030 TSC2 TRUE TRUE 1 6
## 3 __mu… CRUK… CRUK0030 U2AF1 TRUE TRUE 1 6
## 4 __mu… CRUK… CRUK0030 TP53 TRUE TRUE 1 6
## 5 __mu… CRUK… CRUK0030 FBXW7 TRUE TRUE 1 6
## 6 __mu… CRUK… CRUK0030 NF1 TRUE TRUE 1 6
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>
##
## $dataset$CRUK0031
## # A tibble: 5 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0031 KEAP1 TRUE TRUE 1 4
## 2 __mu… CRUK… CRUK0031 CDKN2A TRUE TRUE 1 4
## 3 __mu… CRUK… CRUK0031 PRF1 TRUE TRUE 1 4
## 4 __mu… Anno… CRUK0031 FGFR1 TRUE TRUE 1 4
## 5 __mu… CRUK… CRUK0031 NF1 TRUE FALSE 6 1
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>
##
## $dataset$CRUK0032
## # A tibble: 6 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0032 ATM TRUE TRUE 1 4
## 2 __mu… CRUK… CRUK0032 RAD21 TRUE TRUE 1 4
## 3 __mu… CRUK… CRUK0032 U2AF1 TRUE TRUE 1 4
## 4 __mu… CRUK… CRUK0032 RNF43 TRUE TRUE 1 4
## 5 __mu… Anno… CRUK0032 CCND1 TRUE FALSE 4 1
## 6 __mu… CRUK… CRUK0032 ARID1B TRUE FALSE 6 1
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>
##
## $dataset$CRUK0033
## # A tibble: 2 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0033 KEAP1 TRUE TRUE 1 2
## 2 __mu… CRUK… CRUK0033 CTNNB1 TRUE TRUE 1 2
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0034
## # A tibble: 4 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0034 ATM TRUE TRUE 1 3
## 2 __mu… CRUK… CRUK0034 KRAS TRUE TRUE 1 3
## 3 __mu… CRUK… CRUK0034 PLXNB2 TRUE TRUE 1 3
## 4 __mu… CRUK… CRUK0034 MGA TRUE FALSE 4 1
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>
##
## $dataset$CRUK0035
## # A tibble: 3 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0035 TP53 TRUE TRUE 1 2
## 2 __mu… CRUK… CRUK0035 FAS TRUE TRUE 1 2
## 3 __mu… CRUK… CRUK0035 FLT4 TRUE FALSE 4 1
## # … with 5 more variables: CCF <chr>, LN1 <dbl>, R1 <dbl>, R2 <dbl>,
## # R3 <dbl>
##
## $dataset$CRUK0036
## # A tibble: 5 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0036 KRAS TRUE TRUE 1 5
## 2 __mu… CRUK… CRUK0036 PIK3CA TRUE TRUE 1 5
## 3 __mu… CRUK… CRUK0036 KEAP1 TRUE TRUE 1 5
## 4 __mu… CRUK… CRUK0036 ARHGAP35 TRUE TRUE 1 5
## 5 __mu… Anno… CRUK0036 TERT TRUE TRUE 1 5
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>
##
## $dataset$CRUK0037
## # A tibble: 3 x 14
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0037 NCOA6 TRUE TRUE 1 3
## 2 __mu… CRUK… CRUK0037 CREBBP TRUE TRUE 1 3
## 3 __mu… CRUK… CRUK0037 KRAS TRUE TRUE 1 3
## # … with 6 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>, R5 <dbl>
##
## $dataset$CRUK0038
## # A tibble: 2 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0038 KRAS TRUE TRUE 1 1
## 2 __mu… CRUK… CRUK0038 KMT2D TRUE FALSE 3 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0039
## # A tibble: 4 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0039 KRAS TRUE TRUE 1 4
## 2 __mu… CRUK… CRUK0039 CMTR2 TRUE TRUE 1 4
## 3 __mu… CRUK… CRUK0039 NF1 TRUE TRUE 1 4
## 4 __mu… CRUK… CRUK0039 PHOX2B TRUE TRUE 1 4
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>
##
## $dataset$CRUK0040
## # A tibble: 4 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0040 NCOR1 TRUE TRUE 1 4
## 2 __mu… CRUK… CRUK0040 RAD21 TRUE TRUE 1 4
## 3 __mu… CRUK… CRUK0040 KRAS TRUE TRUE 1 4
## 4 __mu… CRUK… CRUK0040 GATA3 TRUE TRUE 1 4
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0041
## # A tibble: 3 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0041 BRAF TRUE TRUE 1 3
## 2 __mu… Anno… CRUK0041 TERT TRUE TRUE 1 3
## 3 __mu… Anno… CRUK0041 EGFR TRUE TRUE 1 3
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>
##
## $dataset$CRUK0042
## # A tibble: 1 x 10
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0042 KRAS TRUE TRUE 1 1
## # … with 2 more variables: CCF <chr>, R1 <dbl>
##
## $dataset$CRUK0043
## # A tibble: 1 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0043 MET TRUE TRUE 1 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0044
## # A tibble: 1 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0044 KRAS TRUE TRUE 1 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0045
## # A tibble: 1 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0045 BAP1 TRUE TRUE 1 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R3 <dbl>
##
## $dataset$CRUK0046
## # A tibble: 2 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0046 KEAP1 TRUE TRUE 1 2
## 2 __mu… CRUK… CRUK0046 APC TRUE TRUE 1 2
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>
##
## $dataset$CRUK0047
## # A tibble: 4 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0047 STK11 TRUE TRUE 1 4
## 2 __mu… CRUK… CRUK0047 APC TRUE TRUE 1 4
## 3 __mu… CRUK… CRUK0047 KRAS TRUE TRUE 1 4
## 4 __mu… Anno… CRUK0047 MYC TRUE TRUE 1 4
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0048
## # A tibble: 7 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0048 APC TRUE TRUE 1 7
## 2 __mu… CRUK… CRUK0048 PRDM1 TRUE TRUE 1 7
## 3 __mu… CRUK… CRUK0048 ARHGAP35 TRUE TRUE 1 7
## 4 __mu… CRUK… CRUK0048 TP53 TRUE TRUE 1 7
## 5 __mu… CRUK… CRUK0048 BRAF TRUE TRUE 1 7
## 6 __mu… Anno… CRUK0048 EGFR TRUE TRUE 1 7
## 7 __mu… Anno… CRUK0048 MYC TRUE TRUE 1 7
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>
##
## $dataset$CRUK0049
## # A tibble: 5 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0049 RB1 TRUE TRUE 1 5
## 2 __mu… CRUK… CRUK0049 TP53 TRUE TRUE 1 5
## 3 __mu… CRUK… CRUK0049 COL2A1 TRUE TRUE 1 5
## 4 __mu… Anno… CRUK0049 EGFR TRUE TRUE 1 5
## 5 __mu… Anno… CRUK0049 KRAS TRUE TRUE 1 5
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0050
## # A tibble: 3 x 14
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0050 KRAS TRUE TRUE 1 3
## 2 __mu… CRUK… CRUK0050 STK11 TRUE TRUE 1 3
## 3 __mu… Anno… CRUK0050 MYC TRUE TRUE 1 3
## # … with 6 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>, R5 <dbl>
##
## $dataset$CRUK0051
## # A tibble: 5 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0051 KRAS TRUE TRUE 1 4
## 2 __mu… CRUK… CRUK0051 FBXW7 TRUE TRUE 1 4
## 3 __mu… CRUK… CRUK0051 TP53 TRUE TRUE 1 4
## 4 __mu… Anno… CRUK0051 EGFR TRUE TRUE 1 4
## 5 __mu… CRUK… CRUK0051 EP300 TRUE FALSE 3 1
## # … with 4 more variables: CCF <chr>, R2 <dbl>, R3 <dbl>, R4 <dbl>
##
## $dataset$CRUK0052
## # A tibble: 9 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0052 KMT2D TRUE TRUE 1 8
## 2 __mu… CRUK… CRUK0052 KRAS TRUE TRUE 1 8
## 3 __mu… CRUK… CRUK0052 NOTCH2 TRUE TRUE 1 8
## 4 __mu… CRUK… CRUK0052 MGA TRUE TRUE 1 8
## 5 __mu… CRUK… CRUK0052 KEAP1 TRUE TRUE 1 8
## 6 __mu… CRUK… CRUK0052 TP53 TRUE TRUE 1 8
## 7 __mu… CRUK… CRUK0052 NF1 TRUE TRUE 1 8
## 8 __mu… CRUK… CRUK0052 SGK223 TRUE TRUE 1 8
## 9 __mu… CRUK… CRUK0052 UBR5 TRUE FALSE 2 1
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R3 <dbl>, R4 <dbl>
##
## $dataset$CRUK0054
## # A tibble: 1 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0054 EGFR TRUE TRUE 1 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0055
## # A tibble: 3 x 10
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0055 FANCM TRUE TRUE 1 2
## 2 __mu… CRUK… CRUK0055 UBR5 TRUE TRUE 1 2
## 3 __mu… CRUK… CRUK0055 FAT1 TRUE FALSE 2 1
## # … with 2 more variables: CCF <chr>, R2 <dbl>
##
## $dataset$CRUK0056
## # A tibble: 3 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0056 RASA1 TRUE TRUE 1 2
## 2 __mu… CRUK… CRUK0056 CREBBP TRUE TRUE 1 2
## 3 __mu… CRUK… CRUK0056 TP53 TRUE FALSE 3 1
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>
##
## $dataset$CRUK0057
## # A tibble: 5 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0057 KRAS TRUE TRUE 1 5
## 2 __mu… CRUK… CRUK0057 SMARCA4 TRUE TRUE 1 5
## 3 __mu… CRUK… CRUK0057 TSC2 TRUE TRUE 1 5
## 4 __mu… CRUK… CRUK0057 DNM2 TRUE TRUE 1 5
## 5 __mu… Anno… CRUK0057 TERT TRUE TRUE 1 5
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0058
## # A tibble: 2 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0058 TP53 TRUE TRUE 1 2
## 2 __mu… CRUK… CRUK0058 EGFR TRUE TRUE 1 2
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0059
## # A tibble: 1 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0059 KRAS TRUE TRUE 1 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0060
## # A tibble: 11 x 10
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0060 SERPINB13 TRUE TRUE 1 11
## 2 __mu… CRUK… CRUK0060 ARID2 TRUE TRUE 1 11
## 3 __mu… CRUK… CRUK0060 COL5A2 TRUE TRUE 1 11
## 4 __mu… CRUK… CRUK0060 FANCM TRUE TRUE 1 11
## 5 __mu… CRUK… CRUK0060 PHOX2B TRUE TRUE 1 11
## 6 __mu… CRUK… CRUK0060 COL2A1 TRUE TRUE 1 11
## 7 __mu… CRUK… CRUK0060 RASA1 TRUE TRUE 1 11
## 8 __mu… CRUK… CRUK0060 NF1 TRUE TRUE 1 11
## 9 __mu… CRUK… CRUK0060 NCOA6 TRUE TRUE 1 11
## 10 __mu… CRUK… CRUK0060 NOTCH2 TRUE TRUE 1 11
## 11 __mu… CRUK… CRUK0060 KMT2C TRUE TRUE 1 11
## # … with 2 more variables: CCF <chr>, R1 <dbl>
##
## $dataset$CRUK0061
## # A tibble: 1 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0061 STK11 TRUE TRUE 1 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0062
## # A tibble: 7 x 16
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0062 FAS TRUE FALSE 1 1
## 2 __mu… CRUK… CRUK0062 PLXNB2 TRUE FALSE 2 1
## 3 __mu… CRUK… CRUK0062 TP53 TRUE TRUE 4 4
## 4 __mu… Anno… CRUK0062 PIK3CA TRUE TRUE 4 4
## 5 __mu… Anno… CRUK0062 SOX2 TRUE TRUE 4 4
## 6 __mu… Anno… CRUK0062 CCND1 TRUE TRUE 4 4
## 7 __mu… CRUK… CRUK0062 UBR5 TRUE FALSE 16 1
## # … with 8 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>, R5 <dbl>, R6 <dbl>, R7 <dbl>
##
## $dataset$CRUK0063
## # A tibble: 11 x 14
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0063 NF1 TRUE FALSE 1 2
## 2 __mu… CRUK… CRUK0063 CYLD TRUE FALSE 1 2
## 3 __mu… CRUK… CRUK0063 PIK3CA TRUE TRUE 2 7
## 4 __mu… CRUK… CRUK0063 TP53 TRUE TRUE 2 7
## 5 __mu… CRUK… CRUK0063 FBXW7 TRUE TRUE 2 7
## 6 __mu… CRUK… CRUK0063 CDKN2A TRUE TRUE 2 7
## 7 __mu… Anno… CRUK0063 SOX2 TRUE TRUE 2 7
## 8 __mu… Anno… CRUK0063 TERT TRUE TRUE 2 7
## 9 __mu… Anno… CRUK0063 PRF1 TRUE TRUE 2 7
## 10 __mu… CRUK… CRUK0063 FANCM TRUE FALSE 6 1
## 11 __mu… CRUK… CRUK0063 EP300 TRUE FALSE 10 1
## # … with 6 more variables: CCF <chr>, R3 <dbl>, R4 <dbl>, R5 <dbl>,
## # R6 <dbl>, R7 <dbl>
##
## $dataset$CRUK0064
## # A tibble: 3 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0064 TP53 TRUE TRUE 1 1
## 2 __mu… CRUK… CRUK0064 MLH1 TRUE FALSE 2 2
## 3 __mu… CRUK… CRUK0064 FAT1 TRUE FALSE 2 2
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0065
## # A tibble: 9 x 15
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0065 TP53 TRUE TRUE 1 4
## 2 __mu… CRUK… CRUK0065 NFE2L2 TRUE TRUE 1 4
## 3 __mu… Anno… CRUK0065 PIK3CA TRUE TRUE 1 4
## 4 __mu… Anno… CRUK0065 SOX2 TRUE TRUE 1 4
## 5 __mu… CRUK… CRUK0065 MLH1 TRUE FALSE 2 3
## 6 __mu… CRUK… CRUK0065 PTPRC TRUE FALSE 2 3
## 7 __mu… CRUK… CRUK0065 UBR5 TRUE FALSE 2 3
## 8 __mu… CRUK… CRUK0065 NOTCH1 TRUE FALSE 6 2
## 9 __mu… CRUK… CRUK0065 NCOA6 TRUE FALSE 6 2
## # … with 7 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>, R5 <dbl>, R6 <dbl>
##
## $dataset$CRUK0066
## # A tibble: 8 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0066 TP53 TRUE TRUE 1 7
## 2 __mu… CRUK… CRUK0066 NOTCH1 TRUE TRUE 1 7
## 3 __mu… CRUK… CRUK0066 CDKN2A TRUE TRUE 1 7
## 4 __mu… CRUK… CRUK0066 WRN TRUE TRUE 1 7
## 5 __mu… Anno… CRUK0066 PDGFRA TRUE TRUE 1 7
## 6 __mu… Anno… CRUK0066 TERT TRUE TRUE 1 7
## 7 __mu… Anno… CRUK0066 NCOA6 TRUE TRUE 1 7
## 8 __mu… CRUK… CRUK0066 COL5A2 TRUE FALSE 9 1
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>
##
## $dataset$CRUK0067
## # A tibble: 6 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0067 NOTCH1 TRUE TRUE 1 5
## 2 __mu… CRUK… CRUK0067 TP53 TRUE TRUE 1 5
## 3 __mu… Anno… CRUK0067 PIK3CA TRUE TRUE 1 5
## 4 __mu… Anno… CRUK0067 SOX2 TRUE TRUE 1 5
## 5 __mu… Anno… CRUK0067 CDKN2A TRUE TRUE 1 5
## 6 __mu… CRUK… CRUK0067 NFE2L2 TRUE FALSE 2 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R3 <dbl>
##
## $dataset$CRUK0068
## # A tibble: 8 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0068 TP53 TRUE TRUE 1 5
## 2 __mu… CRUK… CRUK0068 PTEN TRUE TRUE 1 5
## 3 __mu… CRUK… CRUK0068 KMT2D TRUE TRUE 1 5
## 4 __mu… Anno… CRUK0068 PIK3CA TRUE TRUE 1 5
## 5 __mu… Anno… CRUK0068 SOX2 TRUE TRUE 1 5
## 6 __mu… CRUK… CRUK0068 MGA TRUE FALSE 3 1
## 7 __mu… CRUK… CRUK0068 SETD2 TRUE FALSE 4 1
## 8 __mu… Anno… CRUK0068 TERT TRUE FALSE 9 1
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>
##
## $dataset$CRUK0069
## # A tibble: 5 x 14
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0069 TP53 TRUE TRUE 1 4
## 2 __mu… CRUK… CRUK0069 FAT1 TRUE TRUE 1 4
## 3 __mu… Anno… CRUK0069 PDGFRA TRUE TRUE 1 4
## 4 __mu… Anno… CRUK0069 FGFR1 TRUE TRUE 1 4
## 5 __mu… CRUK… CRUK0069 KRAS TRUE FALSE 13 1
## # … with 6 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>, R5 <dbl>
##
## $dataset$CRUK0070
## # A tibble: 6 x 14
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0070 DNM2 TRUE TRUE 1 4
## 2 __mu… CRUK… CRUK0070 TP53 TRUE TRUE 1 4
## 3 __mu… Anno… CRUK0070 COL5A2 TRUE TRUE 1 4
## 4 __mu… Anno… CRUK0070 SOX2 TRUE TRUE 1 4
## 5 __mu… CRUK… CRUK0070 CBLB TRUE FALSE 2 1
## 6 __mu… Anno… CRUK0070 NFE2L2 TRUE FALSE 3 1
## # … with 6 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R4 <dbl>,
## # R6 <dbl>, R7 <dbl>
##
## $dataset$CRUK0071
## # A tibble: 4 x 15
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0071 CMTR2 TRUE TRUE 1 3
## 2 __mu… Anno… CRUK0071 PIK3CA TRUE TRUE 1 3
## 3 __mu… Anno… CRUK0071 SOX2 TRUE TRUE 1 3
## 4 __mu… CRUK… CRUK0071 UBR5 TRUE FALSE 4 1
## # … with 7 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R5 <dbl>, R6 <dbl>, R7 <dbl>
##
## $dataset$CRUK0072
## # A tibble: 6 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0072 TP53 TRUE TRUE 1 6
## 2 __mu… CRUK… CRUK0072 NFE2L2 TRUE TRUE 1 6
## 3 __mu… Anno… CRUK0072 PIK3CA TRUE TRUE 1 6
## 4 __mu… Anno… CRUK0072 SOX2 TRUE TRUE 1 6
## 5 __mu… Anno… CRUK0072 EGFR TRUE TRUE 1 6
## 6 __mu… Anno… CRUK0072 MYC TRUE TRUE 1 6
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R4 <dbl>
##
## $dataset$CRUK0073
## # A tibble: 9 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0073 CDKN2A TRUE TRUE 1 8
## 2 __mu… CRUK… CRUK0073 DICER1 TRUE TRUE 1 8
## 3 __mu… CRUK… CRUK0073 NFE2L2 TRUE TRUE 1 8
## 4 __mu… CRUK… CRUK0073 FAT1 TRUE TRUE 1 8
## 5 __mu… CRUK… CRUK0073 KMT2D TRUE TRUE 1 8
## 6 __mu… CRUK… CRUK0073 NOTCH2 TRUE TRUE 1 8
## 7 __mu… Anno… CRUK0073 FGFR1 TRUE TRUE 1 8
## 8 __mu… Anno… CRUK0073 MYC TRUE TRUE 1 8
## 9 __mu… CRUK… CRUK0073 PLXNB2 TRUE FALSE 2 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0074
## # A tibble: 6 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0074 TP53 TRUE TRUE 1 5
## 2 __mu… CRUK… CRUK0074 NFE2L2 TRUE TRUE 1 5
## 3 __mu… Anno… CRUK0074 PIK3CA TRUE TRUE 1 5
## 4 __mu… Anno… CRUK0074 SOX2 TRUE TRUE 1 5
## 5 __mu… Anno… CRUK0074 CCND1 TRUE TRUE 1 5
## 6 __mu… CRUK… CRUK0074 UBR5 TRUE FALSE 3 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0075
## # A tibble: 8 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0075 NOTCH1 TRUE TRUE 1 7
## 2 __mu… CRUK… CRUK0075 RASA1 TRUE TRUE 1 7
## 3 __mu… CRUK… CRUK0075 TP53 TRUE TRUE 1 7
## 4 __mu… CRUK… CRUK0075 FAT1 TRUE TRUE 1 7
## 5 __mu… CRUK… CRUK0075 MGA TRUE TRUE 1 7
## 6 __mu… CRUK… CRUK0075 PIK3CA TRUE TRUE 1 7
## 7 __mu… Anno… CRUK0075 FGFR1 TRUE TRUE 1 7
## 8 __mu… CRUK… CRUK0075 NFE2L2 TRUE FALSE 2 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0076
## # A tibble: 8 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0076 SERPINB13 TRUE TRUE 1 6
## 2 __mu… CRUK… CRUK0076 TP53 TRUE TRUE 1 6
## 3 __mu… CRUK… CRUK0076 ARID1B TRUE TRUE 1 6
## 4 __mu… Anno… CRUK0076 PIK3CA TRUE TRUE 1 6
## 5 __mu… Anno… CRUK0076 SOX2 TRUE TRUE 1 6
## 6 __mu… Anno… CRUK0076 FGFR1 TRUE TRUE 1 6
## 7 __mu… CRUK… CRUK0076 NCOR1 TRUE FALSE 2 1
## 8 __mu… CRUK… CRUK0076 COL5A2 TRUE FALSE 3 1
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>
##
## $dataset$CRUK0077
## # A tibble: 3 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0077 TP53 TRUE TRUE 1 3
## 2 __mu… CRUK… CRUK0077 LATS1 TRUE TRUE 1 3
## 3 __mu… CRUK… CRUK0077 KEAP1 TRUE TRUE 1 3
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>
##
## $dataset$CRUK0078
## # A tibble: 5 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0078 PLXNB2 TRUE TRUE 1 5
## 2 __mu… CRUK… CRUK0078 PTEN TRUE TRUE 1 5
## 3 __mu… Anno… CRUK0078 PIK3CA TRUE TRUE 1 5
## 4 __mu… Anno… CRUK0078 SOX2 TRUE TRUE 1 5
## 5 __mu… Anno… CRUK0078 FGFR1 TRUE TRUE 1 5
## # … with 4 more variables: CCF <chr>, R2 <dbl>, R3 <dbl>, R4 <dbl>
##
## $dataset$CRUK0079
## # A tibble: 6 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0079 FAT1 TRUE TRUE 1 6
## 2 __mu… CRUK… CRUK0079 TP53 TRUE TRUE 1 6
## 3 __mu… CRUK… CRUK0079 POLE TRUE TRUE 1 6
## 4 __mu… Anno… CRUK0079 PIK3CA TRUE TRUE 1 6
## 5 __mu… Anno… CRUK0079 SOX2 TRUE TRUE 1 6
## 6 __mu… Anno… CRUK0079 FGFR1 TRUE TRUE 1 6
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>
##
## $dataset$CRUK0080
## # A tibble: 5 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0080 TP53 TRUE TRUE 1 4
## 2 __mu… CRUK… CRUK0080 WT1 TRUE TRUE 1 4
## 3 __mu… Anno… CRUK0080 EGFR TRUE TRUE 1 4
## 4 __mu… Anno… CRUK0080 CCND1 TRUE TRUE 1 4
## 5 __mu… CRUK… CRUK0080 IKZF1 TRUE FALSE 3 1
## # … with 5 more variables: CCF <chr>, R3 <dbl>, R4 <dbl>, R5 <dbl>,
## # R6 <dbl>
##
## $dataset$CRUK0081
## # A tibble: 6 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0081 NOTCH1 TRUE TRUE 1 5
## 2 __mu… CRUK… CRUK0081 TP53 TRUE TRUE 1 5
## 3 __mu… CRUK… CRUK0081 CDKN2A TRUE TRUE 1 5
## 4 __mu… CRUK… CRUK0081 FAT1 TRUE TRUE 1 5
## 5 __mu… CRUK… CRUK0081 FANCC TRUE TRUE 1 5
## 6 __mu… CRUK… CRUK0081 CYLD TRUE FALSE 3 1
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R5 <dbl>
##
## $dataset$CRUK0082
## # A tibble: 8 x 14
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0082 TP53 TRUE TRUE 1 8
## 2 __mu… CRUK… CRUK0082 WT1 TRUE TRUE 1 8
## 3 __mu… CRUK… CRUK0082 PTEN TRUE TRUE 1 8
## 4 __mu… CRUK… CRUK0082 COL5A2 TRUE TRUE 1 8
## 5 __mu… CRUK… CRUK0082 KMT2D TRUE TRUE 1 8
## 6 __mu… Anno… CRUK0082 PIK3CA TRUE TRUE 1 8
## 7 __mu… Anno… CRUK0082 SOX2 TRUE TRUE 1 8
## 8 __mu… Anno… CRUK0082 FGFR1 TRUE TRUE 1 8
## # … with 6 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>, R5 <dbl>
##
## $dataset$CRUK0083
## # A tibble: 7 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0083 TP53 TRUE TRUE 1 7
## 2 __mu… CRUK… CRUK0083 FBXW7 TRUE TRUE 1 7
## 3 __mu… CRUK… CRUK0083 RASA1 TRUE TRUE 1 7
## 4 __mu… Anno… CRUK0083 PIK3CA TRUE TRUE 1 7
## 5 __mu… Anno… CRUK0083 SOX2 TRUE TRUE 1 7
## 6 __mu… Anno… CRUK0083 FGFR1 TRUE TRUE 1 7
## 7 __mu… Anno… CRUK0083 MYC TRUE TRUE 1 7
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>
##
## $dataset$CRUK0084
## # A tibble: 1 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0084 CREBBP TRUE TRUE 1 1
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>
##
## $dataset$CRUK0085
## # A tibble: 4 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0085 CHEK2 TRUE TRUE 1 4
## 2 __mu… CRUK… CRUK0085 CREBBP TRUE TRUE 1 4
## 3 __mu… CRUK… CRUK0085 LATS1 TRUE TRUE 1 4
## 4 __mu… CRUK… CRUK0085 FANCM TRUE TRUE 1 4
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>
##
## $dataset$CRUK0086
## # A tibble: 3 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0086 TP53 TRUE TRUE 1 3
## 2 __mu… CRUK… CRUK0086 ARID2 TRUE TRUE 1 3
## 3 __mu… Anno… CRUK0086 FAT1 TRUE TRUE 1 3
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R4 <dbl>
##
## $dataset$CRUK0087
## # A tibble: 4 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0087 NFE2L2 TRUE TRUE 1 4
## 2 __mu… CRUK… CRUK0087 TP53 TRUE TRUE 1 4
## 3 __mu… CRUK… CRUK0087 ASXL1 TRUE TRUE 1 4
## 4 __mu… CRUK… CRUK0087 PIK3CA TRUE TRUE 1 4
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>
##
## $dataset$CRUK0088
## # A tibble: 2 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0088 CUX1 TRUE TRUE 1 2
## 2 __mu… CRUK… CRUK0088 TP53 TRUE TRUE 1 2
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0089
## # A tibble: 3 x 10
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0089 PIK3CA TRUE TRUE 1 3
## 2 __mu… CRUK… CRUK0089 SMAD4 TRUE TRUE 1 3
## 3 __mu… CRUK… CRUK0089 KEAP1 TRUE TRUE 1 3
## # … with 2 more variables: CCF <chr>, R2 <dbl>
##
## $dataset$CRUK0090
## # A tibble: 5 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0090 CDKN2A TRUE TRUE 1 5
## 2 __mu… CRUK… CRUK0090 NCOA6 TRUE TRUE 1 5
## 3 __mu… CRUK… CRUK0090 CUX1 TRUE TRUE 1 5
## 4 __mu… CRUK… CRUK0090 COL2A1 TRUE TRUE 1 5
## 5 __mu… CRUK… CRUK0090 NRAS TRUE TRUE 1 5
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0091
## # A tibble: 3 x 10
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0091 TP53 TRUE TRUE 1 3
## 2 __mu… CRUK… CRUK0091 SMARCA4 TRUE TRUE 1 3
## 3 __mu… CRUK… CRUK0091 CDKN2A TRUE TRUE 1 3
## # … with 2 more variables: CCF <chr>, R2 <dbl>
##
## $dataset$CRUK0092
## # A tibble: 5 x 10
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0092 TP53 TRUE TRUE 1 5
## 2 __mu… CRUK… CRUK0092 SMAD4 TRUE TRUE 1 5
## 3 __mu… CRUK… CRUK0092 RASA1 TRUE TRUE 1 5
## 4 __mu… CRUK… CRUK0092 CBLB TRUE TRUE 1 5
## 5 __mu… CRUK… CRUK0092 PIK3CA TRUE TRUE 1 5
## # … with 2 more variables: CCF <chr>, R1 <dbl>
##
## $dataset$CRUK0093
## # A tibble: 7 x 10
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0093 DICER1 TRUE TRUE 1 7
## 2 __mu… CRUK… CRUK0093 CDKN2A TRUE TRUE 1 7
## 3 __mu… CRUK… CRUK0093 COL2A1 TRUE TRUE 1 7
## 4 __mu… CRUK… CRUK0093 GATA3 TRUE TRUE 1 7
## 5 __mu… CRUK… CRUK0093 CIC TRUE TRUE 1 7
## 6 __mu… CRUK… CRUK0093 COL5A2 TRUE TRUE 1 7
## 7 __mu… CRUK… CRUK0093 TP53 TRUE TRUE 1 7
## # … with 2 more variables: CCF <chr>, R1 <dbl>
##
## $dataset$CRUK0094
## # A tibble: 2 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0094 SMARCA4 TRUE TRUE 1 2
## 2 __mu… Anno… CRUK0094 TERT TRUE TRUE 1 2
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>
##
## $dataset$CRUK0095
## # A tibble: 3 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0095 TP53 TRUE TRUE 1 3
## 2 __mu… CRUK… CRUK0095 NF1 TRUE TRUE 1 3
## 3 __mu… CRUK… CRUK0095 RASA1 TRUE TRUE 1 3
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>
##
## $dataset$CRUK0096
## # A tibble: 3 x 16
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0096 KRAS TRUE TRUE 1 3
## 2 __mu… CRUK… CRUK0096 SGK223 TRUE TRUE 1 3
## 3 __mu… CRUK… CRUK0096 MAP3K1 TRUE TRUE 1 3
## # … with 8 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>,
## # R4 <dbl>, R5 <dbl>, R6 <dbl>, R7 <dbl>
##
## $dataset$CRUK0097
## # A tibble: 2 x 11
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0097 TP53 TRUE TRUE 1 2
## 2 __mu… CRUK… CRUK0097 PTEN TRUE TRUE 1 2
## # … with 3 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>
##
## $dataset$CRUK0098
## # A tibble: 3 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0098 TP53 TRUE TRUE 1 2
## 2 __mu… Anno… CRUK0098 PTEN TRUE TRUE 1 2
## 3 __mu… CRUK… CRUK0098 UBR5 TRUE FALSE 3 1
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>
##
## $dataset$CRUK0099
## # A tibble: 3 x 13
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0099 STK11 TRUE TRUE 1 3
## 2 __mu… CRUK… CRUK0099 KEAP1 TRUE TRUE 1 3
## 3 __mu… CRUK… CRUK0099 TP53 TRUE TRUE 1 3
## # … with 5 more variables: CCF <chr>, R1 <dbl>, R3 <dbl>, R6 <dbl>,
## # R7 <dbl>
##
## $dataset$CRUK0100
## # A tibble: 6 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0100 TP53 TRUE TRUE 1 6
## 2 __mu… CRUK… CRUK0100 PHOX2B TRUE TRUE 1 6
## 3 __mu… CRUK… CRUK0100 COL5A2 TRUE TRUE 1 6
## 4 __mu… CRUK… CRUK0100 STK11 TRUE TRUE 1 6
## 5 __mu… CRUK… CRUK0100 SPEN TRUE TRUE 1 6
## 6 __mu… Anno… CRUK0100 CDKN2A TRUE TRUE 1 6
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>
##
##
## $CCF
## $CCF$CRUK0001
## # A tibble: 4 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 3 4 TRUE TRUE 0.99 0.99 1
## 2 1 1 TRUE FALSE 0.86 0 0
## 3 2 1 TRUE FALSE 0.19 0 0.95
## 4 5 1 TRUE FALSE 0.82 0 0.71
##
## $CCF$CRUK0002
## # A tibble: 4 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE FALSE 0 0.92 0
## 2 2 2 TRUE TRUE 0.99 0.98 0.99
## 3 5 1 TRUE FALSE 0.78 0 0
## 4 6 1 TRUE FALSE 0.96 0.03 0.98
##
## $CCF$CRUK0003
## # A tibble: 2 x 9
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R6
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.98 0.97 0.87 0.97 0.99
## 2 4 1 TRUE FALSE 0 0 0.49 0 0.01
##
## $CCF$CRUK0004
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 2 TRUE FALSE 0 0 0.95 0.01
## 2 2 2 TRUE TRUE 0.99 0.985 0.99 0.98
##
## $CCF$CRUK0005
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 2 5 TRUE TRUE 1 1 0.97 1
## 2 1 1 TRUE FALSE 0 0 0.8 0
##
## $CCF$CRUK0006
## # A tibble: 3 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1
## 2 2 1 TRUE FALSE 0 0.93
## 3 7 1 TRUE FALSE 0.99 0.06
##
## $CCF$CRUK0007
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.98 0.93
##
## $CCF$CRUK0008
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 2 5 TRUE TRUE 0.99 1
## 2 3 1 TRUE FALSE 0.86 0
##
## $CCF$CRUK0009
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 0.99 0.99 0.98 0.99
## 2 2 1 TRUE FALSE 0 0.93 0 0.96
##
## $CCF$CRUK0010
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.95 0.98
##
## $CCF$CRUK0011
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.97 1
## 2 3 1 TRUE FALSE 0.95 0 0
##
## $CCF$CRUK0012
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.98 0.95
##
## $CCF$CRUK0013
## # A tibble: 4 x 9
## cluster nMuts is.driver is.clonal LN1 LN2 R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.99 0.99 0.99 0.99
## 2 2 1 TRUE FALSE 0 0 0 0.75 0
## 3 3 1 TRUE FALSE 0.97 0.96 0.01 0.580 0.94
## 4 4 1 TRUE FALSE 0 0 0.97 0.37 0.01
##
## $CCF$CRUK0014
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.96 0.96
## 2 2 1 TRUE FALSE 0.35 0.01
##
## $CCF$CRUK0015
## # A tibble: 3 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.99 0.99
## 2 2 1 TRUE FALSE 0.94 0.01
## 3 3 1 TRUE FALSE 0.01 0.65
##
## $CCF$CRUK0016
## # A tibble: 5 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 0.99 0.99
## 2 16 2 TRUE FALSE 0.97 0
## 3 10 1 TRUE FALSE 0.34 0.3
## 4 2 1 TRUE FALSE 0.53 0
## 5 6 1 TRUE FALSE 0.31 0.53
##
## $CCF$CRUK0017
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 1 1 1 1
## 2 3 1 TRUE FALSE 0 0.94 0.95 0.59
##
## $CCF$CRUK0018
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1
##
## $CCF$CRUK0019
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.97 0.96
##
## $CCF$CRUK0020
## # A tibble: 4 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 7 TRUE TRUE 1 1
## 2 2 1 TRUE FALSE 0.87 0
## 3 3 1 TRUE FALSE 0.9 0.08
## 4 4 1 TRUE FALSE 0 0.85
##
## $CCF$CRUK0021
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 0.99
##
## $CCF$CRUK0022
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.99 0.99
## 2 2 1 TRUE FALSE 0.85 0
##
## $CCF$CRUK0023
## # A tibble: 3 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.99 0.98 0.99 0.95
## 2 4 2 TRUE FALSE 0.01 0.945 0 0
## 3 2 1 TRUE FALSE 0.81 0 0 0
##
## $CCF$CRUK0024
## # A tibble: 3 x 8
## cluster nMuts is.driver is.clonal R1 R3 R4 R6
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1
## 2 3 1 TRUE FALSE 0.88 0.97 0.95 0
## 3 4 1 TRUE FALSE 0.83 0 0 0
##
## $CCF$CRUK0025
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 1 1 1
##
## $CCF$CRUK0026
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 0.98 0.98
##
## $CCF$CRUK0027
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.96 1
## 2 2 1 TRUE FALSE 0 0.99
##
## $CCF$CRUK0028
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.975 0.95
##
## $CCF$CRUK0029
## # A tibble: 1 x 10
## cluster nMuts is.driver is.clonal R2 R4 R5 R6 R7 R8
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 0.99 0.98 1 1 1
##
## $CCF$CRUK0030
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 1 0.98 0.98
##
## $CCF$CRUK0031
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1
## 2 6 1 TRUE FALSE 0.88 0.05 0
##
## $CCF$CRUK0032
## # A tibble: 3 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1
## 2 4 1 TRUE FALSE 0 0.97 0 0.98
## 3 6 1 TRUE FALSE 0 0 0 0.3
##
## $CCF$CRUK0033
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.99 0.98
##
## $CCF$CRUK0034
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 1 1 1
## 2 4 1 TRUE FALSE 0 0.5 0
##
## $CCF$CRUK0035
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal LN1 R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.98 0.98 0.99 0.99
## 2 4 1 TRUE FALSE 0 0.8 0 0.01
##
## $CCF$CRUK0036
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 0.99 0.98 0.97 1
##
## $CCF$CRUK0037
## # A tibble: 1 x 9
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.99 1 1 1 1
##
## $CCF$CRUK0038
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.99
## 2 3 1 TRUE FALSE 0 0.38
##
## $CCF$CRUK0039
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 0.98
##
## $CCF$CRUK0040
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 0.99 0.99
##
## $CCF$CRUK0041
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.98 0.99 0.99 0.99
##
## $CCF$CRUK0042
## # A tibble: 1 x 5
## cluster nMuts is.driver is.clonal R1
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 1 TRUE TRUE 0.91
##
## $CCF$CRUK0043
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.98
##
## $CCF$CRUK0044
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 1 1
##
## $CCF$CRUK0045
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.98 0.98
##
## $CCF$CRUK0046
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 1 0.98 0.995 0.96
##
## $CCF$CRUK0047
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 0.99 1
##
## $CCF$CRUK0048
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 7 TRUE TRUE 1 1 1
##
## $CCF$CRUK0049
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 1 1
##
## $CCF$CRUK0050
## # A tibble: 1 x 9
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.99 0.99 0.99 1 0.99
##
## $CCF$CRUK0051
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1
## 2 3 1 TRUE FALSE 0.97 0 0
##
## $CCF$CRUK0052
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R1 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 8 TRUE TRUE 1 1 1
## 2 2 1 TRUE FALSE 0 0 0.86
##
## $CCF$CRUK0054
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.99
##
## $CCF$CRUK0055
## # A tibble: 2 x 5
## cluster nMuts is.driver is.clonal R2
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 2 TRUE TRUE 1
## 2 2 1 TRUE FALSE 0.32
##
## $CCF$CRUK0056
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 1 1 1
## 2 3 1 TRUE FALSE 0 0.12 0.98
##
## $CCF$CRUK0057
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 1 1
##
## $CCF$CRUK0058
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.98 0.99
##
## $CCF$CRUK0059
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.98
##
## $CCF$CRUK0060
## # A tibble: 1 x 5
## cluster nMuts is.driver is.clonal R1
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 11 TRUE TRUE 1
##
## $CCF$CRUK0061
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 1
##
## $CCF$CRUK0062
## # A tibble: 4 x 11
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5 R6
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 4 4 TRUE TRUE 0.99 0.99 0.98 0.97 0.99 0.99
## 2 1 1 TRUE FALSE 0 0.01 0 0 0 0.94
## 3 16 1 TRUE FALSE 0.93 0.86 0.08 0.02 0.12 0
## 4 2 1 TRUE FALSE 0.84 0.83 0.02 0 0 0
## # … with 1 more variable: R7 <dbl>
##
## $CCF$CRUK0063
## # A tibble: 4 x 9
## cluster nMuts is.driver is.clonal R3 R4 R5 R6 R7
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2 7 TRUE TRUE 0.93 0.99 0.99 0.99 1
## 2 1 2 TRUE FALSE 0 0.99 0.99 0.98 1
## 3 10 1 TRUE FALSE 0 0.99 0.99 0.98 1
## 4 6 1 TRUE FALSE 0 0.02 0.7 0.36 0.55
##
## $CCF$CRUK0064
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 2 2 TRUE FALSE 0.64 0.11
## 2 1 1 TRUE TRUE 1 1
##
## $CCF$CRUK0065
## # A tibble: 3 x 10
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5 R6
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 0.99 0.99 1 1 1
## 2 2 3 TRUE FALSE 0 0 0 0 0.48 0
## 3 6 2 TRUE FALSE 0 0 0 0 0.01 0.83
##
## $CCF$CRUK0066
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 7 TRUE TRUE 0.99 1 1 0.99
## 2 9 1 TRUE FALSE 0 0.91 0.01 0
##
## $CCF$CRUK0067
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 0.99 1
## 2 2 1 TRUE FALSE 0.61 0.83
##
## $CCF$CRUK0068
## # A tibble: 4 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 0.99 1 1 1
## 2 3 1 TRUE FALSE 0.5 0 0 0
## 3 4 1 TRUE FALSE 0.98 0.37 0.99 0.01
## 4 9 1 TRUE FALSE 0 0 0 0.69
##
## $CCF$CRUK0069
## # A tibble: 2 x 9
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1 1
## 2 13 1 TRUE FALSE 0.93 0.42 0.32 0.94 0.96
##
## $CCF$CRUK0070
## # A tibble: 3 x 9
## cluster nMuts is.driver is.clonal R1 R2 R4 R6 R7
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1 1
## 2 2 1 TRUE FALSE 0 0 0 0.95 0.98
## 3 3 1 TRUE FALSE 0.95 0.96 0.98 0 0.01
##
## $CCF$CRUK0071
## # A tibble: 2 x 10
## cluster nMuts is.driver is.clonal R1 R2 R3 R5 R6 R7
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 1 0.99 1 1 1 1
## 2 4 1 TRUE FALSE 0 0.570 0 0 0 0
##
## $CCF$CRUK0072
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 1 0.99 0.99
##
## $CCF$CRUK0073
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 8 TRUE TRUE 1 1
## 2 2 1 TRUE FALSE 0 0.93
##
## $CCF$CRUK0074
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 0.99 1
## 2 3 1 TRUE FALSE 0 0.99
##
## $CCF$CRUK0075
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 7 TRUE TRUE 1 0.99
## 2 2 1 TRUE FALSE 0.15 0.98
##
## $CCF$CRUK0076
## # A tibble: 3 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 1 1 1 1
## 2 2 1 TRUE FALSE 0.93 0 0.28 0
## 3 3 1 TRUE FALSE 0.93 0 0.81 0
##
## $CCF$CRUK0077
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 1 1 1 1
##
## $CCF$CRUK0078
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 1 1 1
##
## $CCF$CRUK0079
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 1 0.99 1 1
##
## $CCF$CRUK0080
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal R3 R4 R5 R6
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1
## 2 3 1 TRUE FALSE 0 0 0.97 0.83
##
## $CCF$CRUK0081
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R5
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 1 0.99
## 2 3 1 TRUE FALSE 0.93 0.01
##
## $CCF$CRUK0082
## # A tibble: 1 x 9
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 8 TRUE TRUE 1 1 1 1 1
##
## $CCF$CRUK0083
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 7 TRUE TRUE 1 1 1 0.99
##
## $CCF$CRUK0084
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 1 1 1 1
##
## $CCF$CRUK0085
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1
##
## $CCF$CRUK0086
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 1 1 1
##
## $CCF$CRUK0087
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1
##
## $CCF$CRUK0088
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 1 1
##
## $CCF$CRUK0089
## # A tibble: 1 x 5
## cluster nMuts is.driver is.clonal R2
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 3 TRUE TRUE 0.99
##
## $CCF$CRUK0090
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 1 1
##
## $CCF$CRUK0091
## # A tibble: 1 x 5
## cluster nMuts is.driver is.clonal R2
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 3 TRUE TRUE 1
##
## $CCF$CRUK0092
## # A tibble: 1 x 5
## cluster nMuts is.driver is.clonal R1
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 5 TRUE TRUE 1
##
## $CCF$CRUK0093
## # A tibble: 1 x 5
## cluster nMuts is.driver is.clonal R1
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 7 TRUE TRUE 0.96
##
## $CCF$CRUK0094
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.98 0.98 0.97 0.99
##
## $CCF$CRUK0095
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.99 0.99 0.98
##
## $CCF$CRUK0096
## # A tibble: 1 x 11
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5 R6
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 1 1 1 1 1 1
## # … with 1 more variable: R7 <dbl>
##
## $CCF$CRUK0097
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.995 0.98
##
## $CCF$CRUK0098
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 1 1 1
## 2 3 1 TRUE FALSE 0.96 0.91 0
##
## $CCF$CRUK0099
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R3 R6 R7
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.95 0.97 0.91 1
##
## $CCF$CRUK0100
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 1 1 1
##
##
## $n
## $n$patients
## [1] 99
##
## $n$variants
## [1] 450
##
## $n$drivers
## [1] 79
##
##
## $CCF_parser
## <srcref: file "/Users/gcaravagna/Documents/Github/revolver/R/CCF_parser.R" chars 25:14 to 36:1>
## <bytecode: 0x7f868f5a9d78>
## <environment: namespace:revolver>
##
## $phylogenies
## $phylogenies$CRUK0001
## $phylogenies$CRUK0001$`1`
## [ ctree - ctree rank 1/3 for CRUK0001 ]
##
## # A tibble: 4 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 3 4 TRUE TRUE 0.99 0.99 1
## 2 1 1 TRUE FALSE 0.86 0 0
## 3 2 1 TRUE FALSE 0.19 0 0.95
## 4 5 1 TRUE FALSE 0.82 0 0.71
##
## Tree shape (drivers annotated)
##
## \-GL
## \-3 [R2] :: TP53, MGA, WRN, EGFR
## |-1 :: NF1
## | \-5 :: PASK
## \-2 :: ARHGAP35
##
## Information transfer
##
## GL ---> TP53
## GL ---> MGA
## GL ---> WRN
## GL ---> EGFR
## TP53 ---> NF1
## MGA ---> NF1
## WRN ---> NF1
## EGFR ---> NF1
## TP53 ---> ARHGAP35
## MGA ---> ARHGAP35
## WRN ---> ARHGAP35
## EGFR ---> ARHGAP35
## NF1 ---> PASK
##
## Tree score 0.111111111111111
##
## $phylogenies$CRUK0001$`2`
## [ ctree - ctree rank 2/3 for CRUK0001 ]
##
## # A tibble: 4 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 3 4 TRUE TRUE 0.99 0.99 1
## 2 1 1 TRUE FALSE 0.86 0 0
## 3 2 1 TRUE FALSE 0.19 0 0.95
## 4 5 1 TRUE FALSE 0.82 0 0.71
##
## Tree shape (drivers annotated)
##
## \-GL
## \-3 [R2] :: TP53, MGA, WRN, EGFR
## |-2 :: ARHGAP35
## | \-5 :: PASK
## \-1 :: NF1
##
## Information transfer
##
## GL ---> TP53
## GL ---> MGA
## GL ---> WRN
## GL ---> EGFR
## TP53 ---> NF1
## MGA ---> NF1
## WRN ---> NF1
## EGFR ---> NF1
## TP53 ---> ARHGAP35
## MGA ---> ARHGAP35
## WRN ---> ARHGAP35
## EGFR ---> ARHGAP35
## ARHGAP35 ---> PASK
##
## Tree score 0.111111111111111
##
## $phylogenies$CRUK0001$`3`
## [ ctree - ctree rank 3/3 for CRUK0001 ]
##
## # A tibble: 4 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 3 4 TRUE TRUE 0.99 0.99 1
## 2 1 1 TRUE FALSE 0.86 0 0
## 3 2 1 TRUE FALSE 0.19 0 0.95
## 4 5 1 TRUE FALSE 0.82 0 0.71
##
## Tree shape (drivers annotated)
##
## \-GL
## \-3 [R2] :: TP53, MGA, WRN, EGFR
## \-1 :: NF1
## \-5 :: PASK
## \-2 :: ARHGAP35
##
## Information transfer
##
## GL ---> TP53
## GL ---> MGA
## GL ---> WRN
## GL ---> EGFR
## TP53 ---> NF1
## MGA ---> NF1
## WRN ---> NF1
## EGFR ---> NF1
## PASK ---> ARHGAP35
## NF1 ---> PASK
##
## Tree score 0.111111111111111
##
##
## $phylogenies$CRUK0002
## $phylogenies$CRUK0002$`1`
## [ ctree - ctree rank 1/2 for CRUK0002 ]
##
## # A tibble: 4 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE FALSE 0 0.92 0
## 2 2 2 TRUE TRUE 0.99 0.98 0.99
## 3 5 1 TRUE FALSE 0.78 0 0
## 4 6 1 TRUE FALSE 0.96 0.03 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-2 :: MET, TERT
## |-6 :: EP300
## | \-5 :: NF1
## \-1 :: RB1, IKZF1, KRAS
##
## Information transfer
##
## MET ---> RB1
## MET ---> IKZF1
## MET ---> KRAS
## TERT ---> RB1
## TERT ---> IKZF1
## TERT ---> KRAS
## GL ---> MET
## GL ---> TERT
## EP300 ---> NF1
## MET ---> EP300
## TERT ---> EP300
##
## Tree score 0.75
##
## $phylogenies$CRUK0002$`2`
## [ ctree - ctree rank 2/2 for CRUK0002 ]
##
## # A tibble: 4 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE FALSE 0 0.92 0
## 2 2 2 TRUE TRUE 0.99 0.98 0.99
## 3 5 1 TRUE FALSE 0.78 0 0
## 4 6 1 TRUE FALSE 0.96 0.03 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-2 :: MET, TERT
## \-1 :: RB1, IKZF1, KRAS
## \-6 :: EP300
## \-5 :: NF1
##
## Information transfer
##
## MET ---> RB1
## MET ---> IKZF1
## MET ---> KRAS
## TERT ---> RB1
## TERT ---> IKZF1
## TERT ---> KRAS
## GL ---> MET
## GL ---> TERT
## EP300 ---> NF1
## RB1 ---> EP300
## IKZF1 ---> EP300
## KRAS ---> EP300
##
## Tree score 0.0833333333333333
##
##
## $phylogenies$CRUK0003
## $phylogenies$CRUK0003$`1`
## [ ctree - ctree rank 1/1 for CRUK0003 ]
##
## # A tibble: 2 x 9
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R6
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.98 0.97 0.87 0.97 0.99
## 2 4 1 TRUE FALSE 0 0 0.49 0 0.01
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R4] :: PIK3CA, EGFR, CDKN2A
## \-4 :: CTNNB1
##
## Information transfer
##
## GL ---> PIK3CA
## GL ---> EGFR
## GL ---> CDKN2A
## PIK3CA ---> CTNNB1
## EGFR ---> CTNNB1
## CDKN2A ---> CTNNB1
##
## Tree score 1
##
##
## $phylogenies$CRUK0004
## $phylogenies$CRUK0004$`1`
## [ ctree - ctree rank 1/1 for CRUK0004 ]
##
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 2 TRUE FALSE 0 0 0.95 0.01
## 2 2 2 TRUE TRUE 0.99 0.985 0.99 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-2 [R1, R2] :: TP53, EGFR
## \-1 :: SMAD4, NOTCH1
##
## Information transfer
##
## TP53 ---> SMAD4
## TP53 ---> NOTCH1
## EGFR ---> SMAD4
## EGFR ---> NOTCH1
## GL ---> TP53
## GL ---> EGFR
##
## Tree score 1
##
##
## $phylogenies$CRUK0005
## $phylogenies$CRUK0005$`1`
## [ ctree - ctree rank 1/1 for CRUK0005 ]
##
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 2 5 TRUE TRUE 1 1 0.97 1
## 2 1 1 TRUE FALSE 0 0 0.8 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-2 [R1, R2, R4] :: CMTR2, TP53, BRAF, PASK, TERT
## \-1 :: NRAS
##
## Information transfer
##
## GL ---> CMTR2
## GL ---> TP53
## GL ---> BRAF
## GL ---> PASK
## GL ---> TERT
## CMTR2 ---> NRAS
## TP53 ---> NRAS
## BRAF ---> NRAS
## PASK ---> NRAS
## TERT ---> NRAS
##
## Tree score 1
##
##
## $phylogenies$CRUK0006
## $phylogenies$CRUK0006$`1`
## [ ctree - ctree rank 1/2 for CRUK0006 ]
##
## # A tibble: 3 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1
## 2 2 1 TRUE FALSE 0 0.93
## 3 7 1 TRUE FALSE 0.99 0.06
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: PLXNB2, TP53, KEAP1, TERT
## |-7 :: FANCC
## \-2 :: MAP3K1
##
## Information transfer
##
## GL ---> PLXNB2
## GL ---> TP53
## GL ---> KEAP1
## GL ---> TERT
## PLXNB2 ---> MAP3K1
## TP53 ---> MAP3K1
## KEAP1 ---> MAP3K1
## TERT ---> MAP3K1
## PLXNB2 ---> FANCC
## TP53 ---> FANCC
## KEAP1 ---> FANCC
## TERT ---> FANCC
##
## Tree score 0.666666666666667
##
## $phylogenies$CRUK0006$`2`
## [ ctree - ctree rank 2/2 for CRUK0006 ]
##
## # A tibble: 3 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1
## 2 2 1 TRUE FALSE 0 0.93
## 3 7 1 TRUE FALSE 0.99 0.06
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: PLXNB2, TP53, KEAP1, TERT
## \-2 :: MAP3K1
## \-7 :: FANCC
##
## Information transfer
##
## GL ---> PLXNB2
## GL ---> TP53
## GL ---> KEAP1
## GL ---> TERT
## PLXNB2 ---> MAP3K1
## TP53 ---> MAP3K1
## KEAP1 ---> MAP3K1
## TERT ---> MAP3K1
## MAP3K1 ---> FANCC
##
## Tree score 0.166666666666667
##
##
## $phylogenies$CRUK0007
## $phylogenies$CRUK0007$`1`
## [ ctree - ctree rank 1/1 for CRUK0007 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.98 0.93
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: PIK3CA, EGFR, SGK223
##
## Information transfer
##
## GL ---> PIK3CA
## GL ---> EGFR
## GL ---> SGK223
##
## Tree score 1
##
##
## $phylogenies$CRUK0008
## $phylogenies$CRUK0008$`1`
## [ ctree - ctree rank 1/1 for CRUK0008 ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 2 5 TRUE TRUE 0.99 1
## 2 3 1 TRUE FALSE 0.86 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-2 [R2] :: KEAP1, STK11, PRDM1, U2AF1, MYC
## \-3 :: ARID2
##
## Information transfer
##
## GL ---> KEAP1
## GL ---> STK11
## GL ---> PRDM1
## GL ---> U2AF1
## GL ---> MYC
## KEAP1 ---> ARID2
## STK11 ---> ARID2
## PRDM1 ---> ARID2
## U2AF1 ---> ARID2
## MYC ---> ARID2
##
## Tree score 1
##
##
## $phylogenies$CRUK0009
## $phylogenies$CRUK0009$`1`
## [ ctree - ctree rank 1/1 for CRUK0009 ]
##
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 0.99 0.99 0.98 0.99
## 2 2 1 TRUE FALSE 0 0.93 0 0.96
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R3] :: BRAF, TP53, ARHGAP35, KMT2C, NFE2L2, MET
## \-2 :: TERT
##
## Information transfer
##
## GL ---> BRAF
## GL ---> TP53
## GL ---> ARHGAP35
## GL ---> KMT2C
## GL ---> NFE2L2
## GL ---> MET
## BRAF ---> TERT
## TP53 ---> TERT
## ARHGAP35 ---> TERT
## KMT2C ---> TERT
## NFE2L2 ---> TERT
## MET ---> TERT
##
## Tree score 1
##
##
## $phylogenies$CRUK0010
## $phylogenies$CRUK0010$`1`
## [ ctree - ctree rank 1/1 for CRUK0010 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.95 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: SETD2, EGFR, TERT
##
## Information transfer
##
## GL ---> SETD2
## GL ---> EGFR
## GL ---> TERT
##
## Tree score 1
##
##
## $phylogenies$CRUK0011
## $phylogenies$CRUK0011$`1`
## [ ctree - ctree rank 1/1 for CRUK0011 ]
##
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.97 1
## 2 3 1 TRUE FALSE 0.95 0 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R2, R3] :: KRAS
## \-3 :: FLT4
##
## Information transfer
##
## GL ---> KRAS
## KRAS ---> FLT4
##
## Tree score 1
##
##
## $phylogenies$CRUK0012
## $phylogenies$CRUK0012$`1`
## [ ctree - ctree rank 1/1 for CRUK0012 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.98 0.95
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: EGFR
##
## Information transfer
##
## GL ---> EGFR
##
## Tree score 1
##
##
## $phylogenies$CRUK0013
## $phylogenies$CRUK0013$`1`
## [ ctree - ctree rank 1/4 for CRUK0013 ]
##
## # A tibble: 4 x 9
## cluster nMuts is.driver is.clonal LN1 LN2 R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.99 0.99 0.99 0.99
## 2 2 1 TRUE FALSE 0 0 0 0.75 0
## 3 3 1 TRUE FALSE 0.97 0.96 0.01 0.580 0.94
## 4 4 1 TRUE FALSE 0 0 0.97 0.37 0.01
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: STK11
## |-3 :: KRAS
## |-4 :: EGFR
## \-2 :: NOTCH1
##
## Information transfer
##
## GL ---> STK11
## STK11 ---> NOTCH1
## STK11 ---> KRAS
## STK11 ---> EGFR
##
## Tree score 0.3
##
## $phylogenies$CRUK0013$`2`
## [ ctree - ctree rank 2/4 for CRUK0013 ]
##
## # A tibble: 4 x 9
## cluster nMuts is.driver is.clonal LN1 LN2 R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.99 0.99 0.99 0.99
## 2 2 1 TRUE FALSE 0 0 0 0.75 0
## 3 3 1 TRUE FALSE 0.97 0.96 0.01 0.580 0.94
## 4 4 1 TRUE FALSE 0 0 0.97 0.37 0.01
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: STK11
## |-3 :: KRAS
## | \-4 :: EGFR
## \-2 :: NOTCH1
##
## Information transfer
##
## GL ---> STK11
## STK11 ---> NOTCH1
## STK11 ---> KRAS
## KRAS ---> EGFR
##
## Tree score 0.24
##
## $phylogenies$CRUK0013$`3`
## [ ctree - ctree rank 3/4 for CRUK0013 ]
##
## # A tibble: 4 x 9
## cluster nMuts is.driver is.clonal LN1 LN2 R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.99 0.99 0.99 0.99
## 2 2 1 TRUE FALSE 0 0 0 0.75 0
## 3 3 1 TRUE FALSE 0.97 0.96 0.01 0.580 0.94
## 4 4 1 TRUE FALSE 0 0 0.97 0.37 0.01
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: STK11
## |-2 :: NOTCH1
## | \-3 :: KRAS
## \-4 :: EGFR
##
## Information transfer
##
## GL ---> STK11
## STK11 ---> NOTCH1
## NOTCH1 ---> KRAS
## STK11 ---> EGFR
##
## Tree score 0.02
##
## $phylogenies$CRUK0013$`4`
## [ ctree - ctree rank 4/4 for CRUK0013 ]
##
## # A tibble: 4 x 9
## cluster nMuts is.driver is.clonal LN1 LN2 R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.99 0.99 0.99 0.99
## 2 2 1 TRUE FALSE 0 0 0 0.75 0
## 3 3 1 TRUE FALSE 0.97 0.96 0.01 0.580 0.94
## 4 4 1 TRUE FALSE 0 0 0.97 0.37 0.01
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: STK11
## \-2 :: NOTCH1
## \-3 :: KRAS
## \-4 :: EGFR
##
## Information transfer
##
## GL ---> STK11
## STK11 ---> NOTCH1
## NOTCH1 ---> KRAS
## KRAS ---> EGFR
##
## Tree score 0.02
##
##
## $phylogenies$CRUK0014
## $phylogenies$CRUK0014$`1`
## [ ctree - ctree rank 1/1 for CRUK0014 ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.96 0.96
## 2 2 1 TRUE FALSE 0.35 0.01
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53, KRAS
## \-2 :: RNF43
##
## Information transfer
##
## GL ---> TP53
## GL ---> KRAS
## TP53 ---> RNF43
## KRAS ---> RNF43
##
## Tree score 1
##
##
## $phylogenies$CRUK0015
## $phylogenies$CRUK0015$`1`
## [ ctree - ctree rank 1/1 for CRUK0015 ]
##
## # A tibble: 3 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.99 0.99
## 2 2 1 TRUE FALSE 0.94 0.01
## 3 3 1 TRUE FALSE 0.01 0.65
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: BAP1, EGFR
## |-2 :: TP53
## \-3 :: RB1
##
## Information transfer
##
## GL ---> BAP1
## GL ---> EGFR
## BAP1 ---> TP53
## EGFR ---> TP53
## BAP1 ---> RB1
## EGFR ---> RB1
##
## Tree score 1
##
##
## $phylogenies$CRUK0016
## $phylogenies$CRUK0016$`1`
## [ ctree - ctree rank 1/13 for CRUK0016 ]
##
## # A tibble: 5 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 0.99 0.99
## 2 16 2 TRUE FALSE 0.97 0
## 3 10 1 TRUE FALSE 0.34 0.3
## 4 2 1 TRUE FALSE 0.53 0
## 5 6 1 TRUE FALSE 0.31 0.53
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53, FAT1, SPEN, CBLB, TERT, CDKN2A
## |-16 :: LATS1, ARID1B
## | \-2 :: ASXL1
## |-10 :: DNM2
## \-6 :: PTPRC
##
## Information transfer
##
## GL ---> TP53
## GL ---> FAT1
## GL ---> SPEN
## GL ---> CBLB
## GL ---> TERT
## GL ---> CDKN2A
## TP53 ---> LATS1
## TP53 ---> ARID1B
## FAT1 ---> LATS1
## FAT1 ---> ARID1B
## SPEN ---> LATS1
## SPEN ---> ARID1B
## CBLB ---> LATS1
## CBLB ---> ARID1B
## TERT ---> LATS1
## TERT ---> ARID1B
## CDKN2A ---> LATS1
## CDKN2A ---> ARID1B
## TP53 ---> DNM2
## FAT1 ---> DNM2
## SPEN ---> DNM2
## CBLB ---> DNM2
## TERT ---> DNM2
## CDKN2A ---> DNM2
## LATS1 ---> ASXL1
## ARID1B ---> ASXL1
## TP53 ---> PTPRC
## FAT1 ---> PTPRC
## SPEN ---> PTPRC
## CBLB ---> PTPRC
## TERT ---> PTPRC
## CDKN2A ---> PTPRC
##
## Tree score 0.03125
##
## $phylogenies$CRUK0016$`2`
## [ ctree - ctree rank 2/13 for CRUK0016 ]
##
## # A tibble: 5 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 0.99 0.99
## 2 16 2 TRUE FALSE 0.97 0
## 3 10 1 TRUE FALSE 0.34 0.3
## 4 2 1 TRUE FALSE 0.53 0
## 5 6 1 TRUE FALSE 0.31 0.53
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53, FAT1, SPEN, CBLB, TERT, CDKN2A
## \-16 :: LATS1, ARID1B
## |-2 :: ASXL1
## | \-10 :: DNM2
## \-6 :: PTPRC
##
## Information transfer
##
## GL ---> TP53
## GL ---> FAT1
## GL ---> SPEN
## GL ---> CBLB
## GL ---> TERT
## GL ---> CDKN2A
## TP53 ---> LATS1
## TP53 ---> ARID1B
## FAT1 ---> LATS1
## FAT1 ---> ARID1B
## SPEN ---> LATS1
## SPEN ---> ARID1B
## CBLB ---> LATS1
## CBLB ---> ARID1B
## TERT ---> LATS1
## TERT ---> ARID1B
## CDKN2A ---> LATS1
## CDKN2A ---> ARID1B
## ASXL1 ---> DNM2
## LATS1 ---> ASXL1
## ARID1B ---> ASXL1
## LATS1 ---> PTPRC
## ARID1B ---> PTPRC
##
## Tree score 0.015625
##
## $phylogenies$CRUK0016$`3`
## [ ctree - ctree rank 3/13 for CRUK0016 ]
##
## # A tibble: 5 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 0.99 0.99
## 2 16 2 TRUE FALSE 0.97 0
## 3 10 1 TRUE FALSE 0.34 0.3
## 4 2 1 TRUE FALSE 0.53 0
## 5 6 1 TRUE FALSE 0.31 0.53
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53, FAT1, SPEN, CBLB, TERT, CDKN2A
## \-16 :: LATS1, ARID1B
## \-2 :: ASXL1
## \-6 :: PTPRC
## \-10 :: DNM2
##
## Information transfer
##
## GL ---> TP53
## GL ---> FAT1
## GL ---> SPEN
## GL ---> CBLB
## GL ---> TERT
## GL ---> CDKN2A
## TP53 ---> LATS1
## TP53 ---> ARID1B
## FAT1 ---> LATS1
## FAT1 ---> ARID1B
## SPEN ---> LATS1
## SPEN ---> ARID1B
## CBLB ---> LATS1
## CBLB ---> ARID1B
## TERT ---> LATS1
## TERT ---> ARID1B
## CDKN2A ---> LATS1
## CDKN2A ---> ARID1B
## PTPRC ---> DNM2
## LATS1 ---> ASXL1
## ARID1B ---> ASXL1
## ASXL1 ---> PTPRC
##
## Tree score 0.015625
##
## $phylogenies$CRUK0016$`4`
## [ ctree - ctree rank 4/13 for CRUK0016 ]
##
## # A tibble: 5 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 0.99 0.99
## 2 16 2 TRUE FALSE 0.97 0
## 3 10 1 TRUE FALSE 0.34 0.3
## 4 2 1 TRUE FALSE 0.53 0
## 5 6 1 TRUE FALSE 0.31 0.53
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53, FAT1, SPEN, CBLB, TERT, CDKN2A
## \-16 :: LATS1, ARID1B
## |-10 :: DNM2
## | \-6 :: PTPRC
## \-2 :: ASXL1
##
## Information transfer
##
## GL ---> TP53
## GL ---> FAT1
## GL ---> SPEN
## GL ---> CBLB
## GL ---> TERT
## GL ---> CDKN2A
## TP53 ---> LATS1
## TP53 ---> ARID1B
## FAT1 ---> LATS1
## FAT1 ---> ARID1B
## SPEN ---> LATS1
## SPEN ---> ARID1B
## CBLB ---> LATS1
## CBLB ---> ARID1B
## TERT ---> LATS1
## TERT ---> ARID1B
## CDKN2A ---> LATS1
## CDKN2A ---> ARID1B
## LATS1 ---> DNM2
## ARID1B ---> DNM2
## LATS1 ---> ASXL1
## ARID1B ---> ASXL1
## DNM2 ---> PTPRC
##
## Tree score 0.015625
##
## $phylogenies$CRUK0016$`5`
## [ ctree - ctree rank 5/13 for CRUK0016 ]
##
## # A tibble: 5 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 0.99 0.99
## 2 16 2 TRUE FALSE 0.97 0
## 3 10 1 TRUE FALSE 0.34 0.3
## 4 2 1 TRUE FALSE 0.53 0
## 5 6 1 TRUE FALSE 0.31 0.53
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53, FAT1, SPEN, CBLB, TERT, CDKN2A
## \-16 :: LATS1, ARID1B
## \-2 :: ASXL1
## \-10 :: DNM2
## \-6 :: PTPRC
##
## Information transfer
##
## GL ---> TP53
## GL ---> FAT1
## GL ---> SPEN
## GL ---> CBLB
## GL ---> TERT
## GL ---> CDKN2A
## TP53 ---> LATS1
## TP53 ---> ARID1B
## FAT1 ---> LATS1
## FAT1 ---> ARID1B
## SPEN ---> LATS1
## SPEN ---> ARID1B
## CBLB ---> LATS1
## CBLB ---> ARID1B
## TERT ---> LATS1
## TERT ---> ARID1B
## CDKN2A ---> LATS1
## CDKN2A ---> ARID1B
## ASXL1 ---> DNM2
## LATS1 ---> ASXL1
## ARID1B ---> ASXL1
## DNM2 ---> PTPRC
##
## Tree score 0.015625
##
## $phylogenies$CRUK0016$`6`
## [ ctree - ctree rank 6/13 for CRUK0016 ]
##
## # A tibble: 5 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 0.99 0.99
## 2 16 2 TRUE FALSE 0.97 0
## 3 10 1 TRUE FALSE 0.34 0.3
## 4 2 1 TRUE FALSE 0.53 0
## 5 6 1 TRUE FALSE 0.31 0.53
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53, FAT1, SPEN, CBLB, TERT, CDKN2A
## |-16 :: LATS1, ARID1B
## | \-2 :: ASXL1
## | \-10 :: DNM2
## \-6 :: PTPRC
##
## Information transfer
##
## GL ---> TP53
## GL ---> FAT1
## GL ---> SPEN
## GL ---> CBLB
## GL ---> TERT
## GL ---> CDKN2A
## TP53 ---> LATS1
## TP53 ---> ARID1B
## FAT1 ---> LATS1
## FAT1 ---> ARID1B
## SPEN ---> LATS1
## SPEN ---> ARID1B
## CBLB ---> LATS1
## CBLB ---> ARID1B
## TERT ---> LATS1
## TERT ---> ARID1B
## CDKN2A ---> LATS1
## CDKN2A ---> ARID1B
## ASXL1 ---> DNM2
## LATS1 ---> ASXL1
## ARID1B ---> ASXL1
## TP53 ---> PTPRC
## FAT1 ---> PTPRC
## SPEN ---> PTPRC
## CBLB ---> PTPRC
## TERT ---> PTPRC
## CDKN2A ---> PTPRC
##
## Tree score 0.015625
##
## $phylogenies$CRUK0016$`7`
## [ ctree - ctree rank 7/13 for CRUK0016 ]
##
## # A tibble: 5 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 0.99 0.99
## 2 16 2 TRUE FALSE 0.97 0
## 3 10 1 TRUE FALSE 0.34 0.3
## 4 2 1 TRUE FALSE 0.53 0
## 5 6 1 TRUE FALSE 0.31 0.53
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53, FAT1, SPEN, CBLB, TERT, CDKN2A
## |-16 :: LATS1, ARID1B
## | |-6 :: PTPRC
## | \-2 :: ASXL1
## \-10 :: DNM2
##
## Information transfer
##
## GL ---> TP53
## GL ---> FAT1
## GL ---> SPEN
## GL ---> CBLB
## GL ---> TERT
## GL ---> CDKN2A
## TP53 ---> LATS1
## TP53 ---> ARID1B
## FAT1 ---> LATS1
## FAT1 ---> ARID1B
## SPEN ---> LATS1
## SPEN ---> ARID1B
## CBLB ---> LATS1
## CBLB ---> ARID1B
## TERT ---> LATS1
## TERT ---> ARID1B
## CDKN2A ---> LATS1
## CDKN2A ---> ARID1B
## TP53 ---> DNM2
## FAT1 ---> DNM2
## SPEN ---> DNM2
## CBLB ---> DNM2
## TERT ---> DNM2
## CDKN2A ---> DNM2
## LATS1 ---> ASXL1
## ARID1B ---> ASXL1
## LATS1 ---> PTPRC
## ARID1B ---> PTPRC
##
## Tree score 0.015625
##
## $phylogenies$CRUK0016$`8`
## [ ctree - ctree rank 8/13 for CRUK0016 ]
##
## # A tibble: 5 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 0.99 0.99
## 2 16 2 TRUE FALSE 0.97 0
## 3 10 1 TRUE FALSE 0.34 0.3
## 4 2 1 TRUE FALSE 0.53 0
## 5 6 1 TRUE FALSE 0.31 0.53
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53, FAT1, SPEN, CBLB, TERT, CDKN2A
## |-10 :: DNM2
## | \-6 :: PTPRC
## \-16 :: LATS1, ARID1B
## \-2 :: ASXL1
##
## Information transfer
##
## GL ---> TP53
## GL ---> FAT1
## GL ---> SPEN
## GL ---> CBLB
## GL ---> TERT
## GL ---> CDKN2A
## TP53 ---> LATS1
## TP53 ---> ARID1B
## FAT1 ---> LATS1
## FAT1 ---> ARID1B
## SPEN ---> LATS1
## SPEN ---> ARID1B
## CBLB ---> LATS1
## CBLB ---> ARID1B
## TERT ---> LATS1
## TERT ---> ARID1B
## CDKN2A ---> LATS1
## CDKN2A ---> ARID1B
## TP53 ---> DNM2
## FAT1 ---> DNM2
## SPEN ---> DNM2
## CBLB ---> DNM2
## TERT ---> DNM2
## CDKN2A ---> DNM2
## LATS1 ---> ASXL1
## ARID1B ---> ASXL1
## DNM2 ---> PTPRC
##
## Tree score 0.015625
##
## $phylogenies$CRUK0016$`9`
## [ ctree - ctree rank 9/13 for CRUK0016 ]
##
## # A tibble: 5 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 0.99 0.99
## 2 16 2 TRUE FALSE 0.97 0
## 3 10 1 TRUE FALSE 0.34 0.3
## 4 2 1 TRUE FALSE 0.53 0
## 5 6 1 TRUE FALSE 0.31 0.53
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53, FAT1, SPEN, CBLB, TERT, CDKN2A
## |-16 :: LATS1, ARID1B
## | |-10 :: DNM2
## | \-2 :: ASXL1
## \-6 :: PTPRC
##
## Information transfer
##
## GL ---> TP53
## GL ---> FAT1
## GL ---> SPEN
## GL ---> CBLB
## GL ---> TERT
## GL ---> CDKN2A
## TP53 ---> LATS1
## TP53 ---> ARID1B
## FAT1 ---> LATS1
## FAT1 ---> ARID1B
## SPEN ---> LATS1
## SPEN ---> ARID1B
## CBLB ---> LATS1
## CBLB ---> ARID1B
## TERT ---> LATS1
## TERT ---> ARID1B
## CDKN2A ---> LATS1
## CDKN2A ---> ARID1B
## LATS1 ---> DNM2
## ARID1B ---> DNM2
## LATS1 ---> ASXL1
## ARID1B ---> ASXL1
## TP53 ---> PTPRC
## FAT1 ---> PTPRC
## SPEN ---> PTPRC
## CBLB ---> PTPRC
## TERT ---> PTPRC
## CDKN2A ---> PTPRC
##
## Tree score 0.015625
##
## $phylogenies$CRUK0016$`10`
## [ ctree - ctree rank 10/13 for CRUK0016 ]
##
## # A tibble: 5 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 0.99 0.99
## 2 16 2 TRUE FALSE 0.97 0
## 3 10 1 TRUE FALSE 0.34 0.3
## 4 2 1 TRUE FALSE 0.53 0
## 5 6 1 TRUE FALSE 0.31 0.53
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53, FAT1, SPEN, CBLB, TERT, CDKN2A
## \-16 :: LATS1, ARID1B
## |-6 :: PTPRC
## | \-10 :: DNM2
## \-2 :: ASXL1
##
## Information transfer
##
## GL ---> TP53
## GL ---> FAT1
## GL ---> SPEN
## GL ---> CBLB
## GL ---> TERT
## GL ---> CDKN2A
## TP53 ---> LATS1
## TP53 ---> ARID1B
## FAT1 ---> LATS1
## FAT1 ---> ARID1B
## SPEN ---> LATS1
## SPEN ---> ARID1B
## CBLB ---> LATS1
## CBLB ---> ARID1B
## TERT ---> LATS1
## TERT ---> ARID1B
## CDKN2A ---> LATS1
## CDKN2A ---> ARID1B
## PTPRC ---> DNM2
## LATS1 ---> ASXL1
## ARID1B ---> ASXL1
## LATS1 ---> PTPRC
## ARID1B ---> PTPRC
##
## Tree score 0.015625
##
## $phylogenies$CRUK0016$`11`
## [ ctree - ctree rank 11/13 for CRUK0016 ]
##
## # A tibble: 5 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 0.99 0.99
## 2 16 2 TRUE FALSE 0.97 0
## 3 10 1 TRUE FALSE 0.34 0.3
## 4 2 1 TRUE FALSE 0.53 0
## 5 6 1 TRUE FALSE 0.31 0.53
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53, FAT1, SPEN, CBLB, TERT, CDKN2A
## |-6 :: PTPRC
## | \-10 :: DNM2
## \-16 :: LATS1, ARID1B
## \-2 :: ASXL1
##
## Information transfer
##
## GL ---> TP53
## GL ---> FAT1
## GL ---> SPEN
## GL ---> CBLB
## GL ---> TERT
## GL ---> CDKN2A
## TP53 ---> LATS1
## TP53 ---> ARID1B
## FAT1 ---> LATS1
## FAT1 ---> ARID1B
## SPEN ---> LATS1
## SPEN ---> ARID1B
## CBLB ---> LATS1
## CBLB ---> ARID1B
## TERT ---> LATS1
## TERT ---> ARID1B
## CDKN2A ---> LATS1
## CDKN2A ---> ARID1B
## PTPRC ---> DNM2
## LATS1 ---> ASXL1
## ARID1B ---> ASXL1
## TP53 ---> PTPRC
## FAT1 ---> PTPRC
## SPEN ---> PTPRC
## CBLB ---> PTPRC
## TERT ---> PTPRC
## CDKN2A ---> PTPRC
##
## Tree score 0.015625
##
## $phylogenies$CRUK0016$`12`
## [ ctree - ctree rank 12/13 for CRUK0016 ]
##
## # A tibble: 5 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 0.99 0.99
## 2 16 2 TRUE FALSE 0.97 0
## 3 10 1 TRUE FALSE 0.34 0.3
## 4 2 1 TRUE FALSE 0.53 0
## 5 6 1 TRUE FALSE 0.31 0.53
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53, FAT1, SPEN, CBLB, TERT, CDKN2A
## \-16 :: LATS1, ARID1B
## |-2 :: ASXL1
## | \-6 :: PTPRC
## \-10 :: DNM2
##
## Information transfer
##
## GL ---> TP53
## GL ---> FAT1
## GL ---> SPEN
## GL ---> CBLB
## GL ---> TERT
## GL ---> CDKN2A
## TP53 ---> LATS1
## TP53 ---> ARID1B
## FAT1 ---> LATS1
## FAT1 ---> ARID1B
## SPEN ---> LATS1
## SPEN ---> ARID1B
## CBLB ---> LATS1
## CBLB ---> ARID1B
## TERT ---> LATS1
## TERT ---> ARID1B
## CDKN2A ---> LATS1
## CDKN2A ---> ARID1B
## LATS1 ---> DNM2
## ARID1B ---> DNM2
## LATS1 ---> ASXL1
## ARID1B ---> ASXL1
## ASXL1 ---> PTPRC
##
## Tree score 0.015625
##
## $phylogenies$CRUK0016$`13`
## [ ctree - ctree rank 13/13 for CRUK0016 ]
##
## # A tibble: 5 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 0.99 0.99
## 2 16 2 TRUE FALSE 0.97 0
## 3 10 1 TRUE FALSE 0.34 0.3
## 4 2 1 TRUE FALSE 0.53 0
## 5 6 1 TRUE FALSE 0.31 0.53
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53, FAT1, SPEN, CBLB, TERT, CDKN2A
## |-16 :: LATS1, ARID1B
## | \-2 :: ASXL1
## | \-6 :: PTPRC
## \-10 :: DNM2
##
## Information transfer
##
## GL ---> TP53
## GL ---> FAT1
## GL ---> SPEN
## GL ---> CBLB
## GL ---> TERT
## GL ---> CDKN2A
## TP53 ---> LATS1
## TP53 ---> ARID1B
## FAT1 ---> LATS1
## FAT1 ---> ARID1B
## SPEN ---> LATS1
## SPEN ---> ARID1B
## CBLB ---> LATS1
## CBLB ---> ARID1B
## TERT ---> LATS1
## TERT ---> ARID1B
## CDKN2A ---> LATS1
## CDKN2A ---> ARID1B
## TP53 ---> DNM2
## FAT1 ---> DNM2
## SPEN ---> DNM2
## CBLB ---> DNM2
## TERT ---> DNM2
## CDKN2A ---> DNM2
## LATS1 ---> ASXL1
## ARID1B ---> ASXL1
## ASXL1 ---> PTPRC
##
## Tree score 0.015625
##
##
## $phylogenies$CRUK0017
## $phylogenies$CRUK0017$`1`
## [ ctree - ctree rank 1/1 for CRUK0017 ]
##
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 1 1 1 1
## 2 3 1 TRUE FALSE 0 0.94 0.95 0.59
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1] :: TP53, ARID1B, ARID2, KEAP1, MYC
## \-3 :: KRAS
##
## Information transfer
##
## GL ---> TP53
## GL ---> ARID1B
## GL ---> ARID2
## GL ---> KEAP1
## GL ---> MYC
## TP53 ---> KRAS
## ARID1B ---> KRAS
## ARID2 ---> KRAS
## KEAP1 ---> KRAS
## MYC ---> KRAS
##
## Tree score 1
##
##
## $phylogenies$CRUK0018
## $phylogenies$CRUK0018$`1`
## [ ctree - ctree rank 1/1 for CRUK0018 ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: CMTR2, KRAS, MGA, COL5A2
##
## Information transfer
##
## GL ---> CMTR2
## GL ---> KRAS
## GL ---> MGA
## GL ---> COL5A2
##
## Tree score 1
##
##
## $phylogenies$CRUK0019
## $phylogenies$CRUK0019$`1`
## [ ctree - ctree rank 1/1 for CRUK0019 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.97 0.96
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: EGFR
##
## Information transfer
##
## GL ---> EGFR
##
## Tree score 1
##
##
## $phylogenies$CRUK0020
## $phylogenies$CRUK0020$`1`
## [ ctree - ctree rank 1/2 for CRUK0020 ]
##
## # A tibble: 4 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 7 TRUE TRUE 1 1
## 2 2 1 TRUE FALSE 0.87 0
## 3 3 1 TRUE FALSE 0.9 0.08
## 4 4 1 TRUE FALSE 0 0.85
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: KEAP1, TP53, MGA, ARID2, COL2A1, PRF1, KRAS
## |-3 :: BAP1
## | \-2 :: PIK3CA
## \-4 :: NCOR1
##
## Information transfer
##
## GL ---> KEAP1
## GL ---> TP53
## GL ---> MGA
## GL ---> ARID2
## GL ---> COL2A1
## GL ---> PRF1
## GL ---> KRAS
## BAP1 ---> PIK3CA
## KEAP1 ---> BAP1
## TP53 ---> BAP1
## MGA ---> BAP1
## ARID2 ---> BAP1
## COL2A1 ---> BAP1
## PRF1 ---> BAP1
## KRAS ---> BAP1
## KEAP1 ---> NCOR1
## TP53 ---> NCOR1
## MGA ---> NCOR1
## ARID2 ---> NCOR1
## COL2A1 ---> NCOR1
## PRF1 ---> NCOR1
## KRAS ---> NCOR1
##
## Tree score 0.666666666666667
##
## $phylogenies$CRUK0020$`2`
## [ ctree - ctree rank 2/2 for CRUK0020 ]
##
## # A tibble: 4 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 7 TRUE TRUE 1 1
## 2 2 1 TRUE FALSE 0.87 0
## 3 3 1 TRUE FALSE 0.9 0.08
## 4 4 1 TRUE FALSE 0 0.85
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: KEAP1, TP53, MGA, ARID2, COL2A1, PRF1, KRAS
## \-4 :: NCOR1
## \-3 :: BAP1
## \-2 :: PIK3CA
##
## Information transfer
##
## GL ---> KEAP1
## GL ---> TP53
## GL ---> MGA
## GL ---> ARID2
## GL ---> COL2A1
## GL ---> PRF1
## GL ---> KRAS
## BAP1 ---> PIK3CA
## NCOR1 ---> BAP1
## KEAP1 ---> NCOR1
## TP53 ---> NCOR1
## MGA ---> NCOR1
## ARID2 ---> NCOR1
## COL2A1 ---> NCOR1
## PRF1 ---> NCOR1
## KRAS ---> NCOR1
##
## Tree score 0.166666666666667
##
##
## $phylogenies$CRUK0021
## $phylogenies$CRUK0021$`1`
## [ ctree - ctree rank 1/1 for CRUK0021 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: EGFR, TP53, CHEK2, CDKN2A
##
## Information transfer
##
## GL ---> EGFR
## GL ---> TP53
## GL ---> CHEK2
## GL ---> CDKN2A
##
## Tree score 1
##
##
## $phylogenies$CRUK0022
## $phylogenies$CRUK0022$`1`
## [ ctree - ctree rank 1/1 for CRUK0022 ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.99 0.99
## 2 2 1 TRUE FALSE 0.85 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R2] :: TP53, EGFR
## \-2 :: CIC
##
## Information transfer
##
## GL ---> TP53
## GL ---> EGFR
## TP53 ---> CIC
## EGFR ---> CIC
##
## Tree score 1
##
##
## $phylogenies$CRUK0023
## $phylogenies$CRUK0023$`1`
## [ ctree - ctree rank 1/1 for CRUK0023 ]
##
## # A tibble: 3 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.99 0.98 0.99 0.95
## 2 4 2 TRUE FALSE 0.01 0.945 0 0
## 3 2 1 TRUE FALSE 0.81 0 0 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R3, R4] :: WRN, KRAS, CDKN2A
## |-2 :: TP53
## \-4 :: PTPRC, KMT2D
##
## Information transfer
##
## GL ---> WRN
## GL ---> KRAS
## GL ---> CDKN2A
## WRN ---> PTPRC
## WRN ---> KMT2D
## KRAS ---> PTPRC
## KRAS ---> KMT2D
## CDKN2A ---> PTPRC
## CDKN2A ---> KMT2D
## WRN ---> TP53
## KRAS ---> TP53
## CDKN2A ---> TP53
##
## Tree score 1
##
##
## $phylogenies$CRUK0024
## $phylogenies$CRUK0024$`1`
## [ ctree - ctree rank 1/1 for CRUK0024 ]
##
## # A tibble: 3 x 8
## cluster nMuts is.driver is.clonal R1 R3 R4 R6
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1
## 2 3 1 TRUE FALSE 0.88 0.97 0.95 0
## 3 4 1 TRUE FALSE 0.83 0 0 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R6] :: TP53, STK11, POLE, EGFR
## \-3 :: ATM
## \-4 :: NCOR1
##
## Information transfer
##
## GL ---> TP53
## GL ---> STK11
## GL ---> POLE
## GL ---> EGFR
## TP53 ---> ATM
## STK11 ---> ATM
## POLE ---> ATM
## EGFR ---> ATM
## ATM ---> NCOR1
##
## Tree score 1
##
##
## $phylogenies$CRUK0025
## $phylogenies$CRUK0025$`1`
## [ ctree - ctree rank 1/1 for CRUK0025 ]
##
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3] :: KRAS, TP53, MGA
##
## Information transfer
##
## GL ---> KRAS
## GL ---> TP53
## GL ---> MGA
##
## Tree score 1
##
##
## $phylogenies$CRUK0026
## $phylogenies$CRUK0026$`1`
## [ ctree - ctree rank 1/1 for CRUK0026 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 0.98 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: TP53, EGFR, RB1, SERPINB13
##
## Information transfer
##
## GL ---> TP53
## GL ---> EGFR
## GL ---> RB1
## GL ---> SERPINB13
##
## Tree score 1
##
##
## $phylogenies$CRUK0027
## $phylogenies$CRUK0027$`1`
## [ ctree - ctree rank 1/1 for CRUK0027 ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.96 1
## 2 2 1 TRUE FALSE 0 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1] :: KRAS, TP53
## \-2 :: PLXNB2
##
## Information transfer
##
## GL ---> KRAS
## GL ---> TP53
## KRAS ---> PLXNB2
## TP53 ---> PLXNB2
##
## Tree score 1
##
##
## $phylogenies$CRUK0028
## $phylogenies$CRUK0028$`1`
## [ ctree - ctree rank 1/1 for CRUK0028 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.975 0.95
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: APC, EGFR
##
## Information transfer
##
## GL ---> APC
## GL ---> EGFR
##
## Tree score 1
##
##
## $phylogenies$CRUK0029
## $phylogenies$CRUK0029$`1`
## [ ctree - ctree rank 1/1 for CRUK0029 ]
##
## # A tibble: 1 x 10
## cluster nMuts is.driver is.clonal R2 R4 R5 R6 R7 R8
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 0.99 0.98 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R2, R4, R5, R6, R7, R8] :: TP53, NRAS, MGA, CCND1
##
## Information transfer
##
## GL ---> TP53
## GL ---> NRAS
## GL ---> MGA
## GL ---> CCND1
##
## Tree score 1
##
##
## $phylogenies$CRUK0030
## $phylogenies$CRUK0030$`1`
## [ ctree - ctree rank 1/1 for CRUK0030 ]
##
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 1 0.98 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3] :: KRAS, TSC2, U2AF1, TP53, FBXW7, NF1
##
## Information transfer
##
## GL ---> KRAS
## GL ---> TSC2
## GL ---> U2AF1
## GL ---> TP53
## GL ---> FBXW7
## GL ---> NF1
##
## Tree score 1
##
##
## $phylogenies$CRUK0031
## $phylogenies$CRUK0031$`1`
## [ ctree - ctree rank 1/1 for CRUK0031 ]
##
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1
## 2 6 1 TRUE FALSE 0.88 0.05 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R3] :: KEAP1, CDKN2A, PRF1, FGFR1
## \-6 :: NF1
##
## Information transfer
##
## GL ---> KEAP1
## GL ---> CDKN2A
## GL ---> PRF1
## GL ---> FGFR1
## KEAP1 ---> NF1
## CDKN2A ---> NF1
## PRF1 ---> NF1
## FGFR1 ---> NF1
##
## Tree score 1
##
##
## $phylogenies$CRUK0032
## $phylogenies$CRUK0032$`1`
## [ ctree - ctree rank 1/1 for CRUK0032 ]
##
## # A tibble: 3 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1
## 2 4 1 TRUE FALSE 0 0.97 0 0.98
## 3 6 1 TRUE FALSE 0 0 0 0.3
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R3] :: ATM, RAD21, U2AF1, RNF43
## \-4 :: CCND1
## \-6 :: ARID1B
##
## Information transfer
##
## GL ---> ATM
## GL ---> RAD21
## GL ---> U2AF1
## GL ---> RNF43
## ATM ---> CCND1
## RAD21 ---> CCND1
## U2AF1 ---> CCND1
## RNF43 ---> CCND1
## CCND1 ---> ARID1B
##
## Tree score 1
##
##
## $phylogenies$CRUK0033
## $phylogenies$CRUK0033$`1`
## [ ctree - ctree rank 1/1 for CRUK0033 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.99 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: KEAP1, CTNNB1
##
## Information transfer
##
## GL ---> KEAP1
## GL ---> CTNNB1
##
## Tree score 1
##
##
## $phylogenies$CRUK0034
## $phylogenies$CRUK0034$`1`
## [ ctree - ctree rank 1/1 for CRUK0034 ]
##
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 1 1 1
## 2 4 1 TRUE FALSE 0 0.5 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R3] :: ATM, KRAS, PLXNB2
## \-4 :: MGA
##
## Information transfer
##
## GL ---> ATM
## GL ---> KRAS
## GL ---> PLXNB2
## ATM ---> MGA
## KRAS ---> MGA
## PLXNB2 ---> MGA
##
## Tree score 1
##
##
## $phylogenies$CRUK0035
## $phylogenies$CRUK0035$`1`
## [ ctree - ctree rank 1/1 for CRUK0035 ]
##
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal LN1 R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.98 0.98 0.99 0.99
## 2 4 1 TRUE FALSE 0 0.8 0 0.01
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [LN1, R2] :: TP53, FAS
## \-4 :: FLT4
##
## Information transfer
##
## GL ---> TP53
## GL ---> FAS
## TP53 ---> FLT4
## FAS ---> FLT4
##
## Tree score 1
##
##
## $phylogenies$CRUK0036
## $phylogenies$CRUK0036$`1`
## [ ctree - ctree rank 1/1 for CRUK0036 ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 0.99 0.98 0.97 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: KRAS, PIK3CA, KEAP1, ARHGAP35, TERT
##
## Information transfer
##
## GL ---> KRAS
## GL ---> PIK3CA
## GL ---> KEAP1
## GL ---> ARHGAP35
## GL ---> TERT
##
## Tree score 1
##
##
## $phylogenies$CRUK0037
## $phylogenies$CRUK0037$`1`
## [ ctree - ctree rank 1/1 for CRUK0037 ]
##
## # A tibble: 1 x 9
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.99 1 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4, R5] :: NCOA6, CREBBP, KRAS
##
## Information transfer
##
## GL ---> NCOA6
## GL ---> CREBBP
## GL ---> KRAS
##
## Tree score 1
##
##
## $phylogenies$CRUK0038
## $phylogenies$CRUK0038$`1`
## [ ctree - ctree rank 1/1 for CRUK0038 ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.99
## 2 3 1 TRUE FALSE 0 0.38
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1] :: KRAS
## \-3 :: KMT2D
##
## Information transfer
##
## GL ---> KRAS
## KRAS ---> KMT2D
##
## Tree score 1
##
##
## $phylogenies$CRUK0039
## $phylogenies$CRUK0039$`1`
## [ ctree - ctree rank 1/1 for CRUK0039 ]
##
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3] :: KRAS, CMTR2, NF1, PHOX2B
##
## Information transfer
##
## GL ---> KRAS
## GL ---> CMTR2
## GL ---> NF1
## GL ---> PHOX2B
##
## Tree score 1
##
##
## $phylogenies$CRUK0040
## $phylogenies$CRUK0040$`1`
## [ ctree - ctree rank 1/1 for CRUK0040 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 0.99 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: NCOR1, RAD21, KRAS, GATA3
##
## Information transfer
##
## GL ---> NCOR1
## GL ---> RAD21
## GL ---> KRAS
## GL ---> GATA3
##
## Tree score 1
##
##
## $phylogenies$CRUK0041
## $phylogenies$CRUK0041$`1`
## [ ctree - ctree rank 1/1 for CRUK0041 ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.98 0.99 0.99 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: BRAF, TERT, EGFR
##
## Information transfer
##
## GL ---> BRAF
## GL ---> TERT
## GL ---> EGFR
##
## Tree score 1
##
##
## $phylogenies$CRUK0042
## $phylogenies$CRUK0042$`1`
## [ ctree - ctree rank 1/1 for CRUK0042 ]
##
## # A tibble: 1 x 5
## cluster nMuts is.driver is.clonal R1
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 1 TRUE TRUE 0.91
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1] :: KRAS
##
## Information transfer
##
## GL ---> KRAS
##
## Tree score 1
##
##
## $phylogenies$CRUK0043
## $phylogenies$CRUK0043$`1`
## [ ctree - ctree rank 1/1 for CRUK0043 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: MET
##
## Information transfer
##
## GL ---> MET
##
## Tree score 1
##
##
## $phylogenies$CRUK0044
## $phylogenies$CRUK0044$`1`
## [ ctree - ctree rank 1/1 for CRUK0044 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: KRAS
##
## Information transfer
##
## GL ---> KRAS
##
## Tree score 1
##
##
## $phylogenies$CRUK0045
## $phylogenies$CRUK0045$`1`
## [ ctree - ctree rank 1/1 for CRUK0045 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.98 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R3] :: BAP1
##
## Information transfer
##
## GL ---> BAP1
##
## Tree score 1
##
##
## $phylogenies$CRUK0046
## $phylogenies$CRUK0046$`1`
## [ ctree - ctree rank 1/1 for CRUK0046 ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 1 0.98 0.995 0.96
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: KEAP1, APC
##
## Information transfer
##
## GL ---> KEAP1
## GL ---> APC
##
## Tree score 1
##
##
## $phylogenies$CRUK0047
## $phylogenies$CRUK0047$`1`
## [ ctree - ctree rank 1/1 for CRUK0047 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 0.99 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: STK11, APC, KRAS, MYC
##
## Information transfer
##
## GL ---> STK11
## GL ---> APC
## GL ---> KRAS
## GL ---> MYC
##
## Tree score 1
##
##
## $phylogenies$CRUK0048
## $phylogenies$CRUK0048$`1`
## [ ctree - ctree rank 1/1 for CRUK0048 ]
##
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 7 TRUE TRUE 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3] :: APC, PRDM1, ARHGAP35, TP53, BRAF, EGFR, MYC
##
## Information transfer
##
## GL ---> APC
## GL ---> PRDM1
## GL ---> ARHGAP35
## GL ---> TP53
## GL ---> BRAF
## GL ---> EGFR
## GL ---> MYC
##
## Tree score 1
##
##
## $phylogenies$CRUK0049
## $phylogenies$CRUK0049$`1`
## [ ctree - ctree rank 1/1 for CRUK0049 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: RB1, TP53, COL2A1, EGFR, KRAS
##
## Information transfer
##
## GL ---> RB1
## GL ---> TP53
## GL ---> COL2A1
## GL ---> EGFR
## GL ---> KRAS
##
## Tree score 1
##
##
## $phylogenies$CRUK0050
## $phylogenies$CRUK0050$`1`
## [ ctree - ctree rank 1/1 for CRUK0050 ]
##
## # A tibble: 1 x 9
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.99 0.99 0.99 1 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4, R5] :: KRAS, STK11, MYC
##
## Information transfer
##
## GL ---> KRAS
## GL ---> STK11
## GL ---> MYC
##
## Tree score 1
##
##
## $phylogenies$CRUK0051
## $phylogenies$CRUK0051$`1`
## [ ctree - ctree rank 1/1 for CRUK0051 ]
##
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1
## 2 3 1 TRUE FALSE 0.97 0 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R3, R4] :: KRAS, FBXW7, TP53, EGFR
## \-3 :: EP300
##
## Information transfer
##
## GL ---> KRAS
## GL ---> FBXW7
## GL ---> TP53
## GL ---> EGFR
## KRAS ---> EP300
## FBXW7 ---> EP300
## TP53 ---> EP300
## EGFR ---> EP300
##
## Tree score 1
##
##
## $phylogenies$CRUK0052
## $phylogenies$CRUK0052$`1`
## [ ctree - ctree rank 1/1 for CRUK0052 ]
##
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R1 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 8 TRUE TRUE 1 1 1
## 2 2 1 TRUE FALSE 0 0 0.86
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R3] :: KMT2D, KRAS, NOTCH2, MGA, KEAP1, TP53, NF1, SGK223
## \-2 :: UBR5
##
## Information transfer
##
## GL ---> KMT2D
## GL ---> KRAS
## GL ---> NOTCH2
## GL ---> MGA
## GL ---> KEAP1
## GL ---> TP53
## GL ---> NF1
## GL ---> SGK223
## KMT2D ---> UBR5
## KRAS ---> UBR5
## NOTCH2 ---> UBR5
## MGA ---> UBR5
## KEAP1 ---> UBR5
## TP53 ---> UBR5
## NF1 ---> UBR5
## SGK223 ---> UBR5
##
## Tree score 1
##
##
## $phylogenies$CRUK0054
## $phylogenies$CRUK0054$`1`
## [ ctree - ctree rank 1/1 for CRUK0054 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: EGFR
##
## Information transfer
##
## GL ---> EGFR
##
## Tree score 1
##
##
## $phylogenies$CRUK0055
## $phylogenies$CRUK0055$`1`
## [ ctree - ctree rank 1/1 for CRUK0055 ]
##
## # A tibble: 2 x 5
## cluster nMuts is.driver is.clonal R2
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 2 TRUE TRUE 1
## 2 2 1 TRUE FALSE 0.32
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: FANCM, UBR5
## \-2 :: FAT1
##
## Information transfer
##
## GL ---> FANCM
## GL ---> UBR5
## FANCM ---> FAT1
## UBR5 ---> FAT1
##
## Tree score 1
##
##
## $phylogenies$CRUK0056
## $phylogenies$CRUK0056$`1`
## [ ctree - ctree rank 1/1 for CRUK0056 ]
##
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 1 1 1
## 2 3 1 TRUE FALSE 0 0.12 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1] :: RASA1, CREBBP
## \-3 :: TP53
##
## Information transfer
##
## GL ---> RASA1
## GL ---> CREBBP
## RASA1 ---> TP53
## CREBBP ---> TP53
##
## Tree score 1
##
##
## $phylogenies$CRUK0057
## $phylogenies$CRUK0057$`1`
## [ ctree - ctree rank 1/1 for CRUK0057 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: KRAS, SMARCA4, TSC2, DNM2, TERT
##
## Information transfer
##
## GL ---> KRAS
## GL ---> SMARCA4
## GL ---> TSC2
## GL ---> DNM2
## GL ---> TERT
##
## Tree score 1
##
##
## $phylogenies$CRUK0058
## $phylogenies$CRUK0058$`1`
## [ ctree - ctree rank 1/1 for CRUK0058 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.98 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: TP53, EGFR
##
## Information transfer
##
## GL ---> TP53
## GL ---> EGFR
##
## Tree score 1
##
##
## $phylogenies$CRUK0059
## $phylogenies$CRUK0059$`1`
## [ ctree - ctree rank 1/1 for CRUK0059 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: KRAS
##
## Information transfer
##
## GL ---> KRAS
##
## Tree score 1
##
##
## $phylogenies$CRUK0060
## $phylogenies$CRUK0060$`1`
## [ ctree - ctree rank 1/1 for CRUK0060 ]
##
## # A tibble: 1 x 5
## cluster nMuts is.driver is.clonal R1
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 11 TRUE TRUE 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1] :: SERPINB13, ARID2, COL5A2, FANCM, PHOX2B, COL2A1, RASA1, NF1, NCOA6, NOTCH2, KMT2C
##
## Information transfer
##
## GL ---> SERPINB13
## GL ---> ARID2
## GL ---> COL5A2
## GL ---> FANCM
## GL ---> PHOX2B
## GL ---> COL2A1
## GL ---> RASA1
## GL ---> NF1
## GL ---> NCOA6
## GL ---> NOTCH2
## GL ---> KMT2C
##
## Tree score 1
##
##
## $phylogenies$CRUK0061
## $phylogenies$CRUK0061$`1`
## [ ctree - ctree rank 1/1 for CRUK0061 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: STK11
##
## Information transfer
##
## GL ---> STK11
##
## Tree score 1
##
##
## $phylogenies$CRUK0062
## $phylogenies$CRUK0062$`1`
## [ ctree - ctree rank 1/2 for CRUK0062 ]
##
## # A tibble: 4 x 11
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5 R6
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 4 4 TRUE TRUE 0.99 0.99 0.98 0.97 0.99 0.99
## 2 1 1 TRUE FALSE 0 0.01 0 0 0 0.94
## 3 16 1 TRUE FALSE 0.93 0.86 0.08 0.02 0.12 0
## 4 2 1 TRUE FALSE 0.84 0.83 0.02 0 0 0
## # … with 1 more variable: R7 <dbl>
##
## Tree shape (drivers annotated)
##
## \-GL
## \-4 :: TP53, PIK3CA, SOX2, CCND1
## |-16 :: UBR5
## | \-2 :: PLXNB2
## \-1 :: FAS
##
## Information transfer
##
## GL ---> TP53
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> CCND1
## TP53 ---> FAS
## PIK3CA ---> FAS
## SOX2 ---> FAS
## CCND1 ---> FAS
## TP53 ---> UBR5
## PIK3CA ---> UBR5
## SOX2 ---> UBR5
## CCND1 ---> UBR5
## UBR5 ---> PLXNB2
##
## Tree score 0.75
##
## $phylogenies$CRUK0062$`2`
## [ ctree - ctree rank 2/2 for CRUK0062 ]
##
## # A tibble: 4 x 11
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5 R6
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 4 4 TRUE TRUE 0.99 0.99 0.98 0.97 0.99 0.99
## 2 1 1 TRUE FALSE 0 0.01 0 0 0 0.94
## 3 16 1 TRUE FALSE 0.93 0.86 0.08 0.02 0.12 0
## 4 2 1 TRUE FALSE 0.84 0.83 0.02 0 0 0
## # … with 1 more variable: R7 <dbl>
##
## Tree shape (drivers annotated)
##
## \-GL
## \-4 :: TP53, PIK3CA, SOX2, CCND1
## |-2 :: PLXNB2
## |-16 :: UBR5
## \-1 :: FAS
##
## Information transfer
##
## GL ---> TP53
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> CCND1
## TP53 ---> FAS
## PIK3CA ---> FAS
## SOX2 ---> FAS
## CCND1 ---> FAS
## TP53 ---> UBR5
## PIK3CA ---> UBR5
## SOX2 ---> UBR5
## CCND1 ---> UBR5
## TP53 ---> PLXNB2
## PIK3CA ---> PLXNB2
## SOX2 ---> PLXNB2
## CCND1 ---> PLXNB2
##
## Tree score 0.178571428571429
##
##
## $phylogenies$CRUK0063
## $phylogenies$CRUK0063$`1`
## [ ctree - ctree rank 1/6 for CRUK0063 ]
##
## # A tibble: 4 x 9
## cluster nMuts is.driver is.clonal R3 R4 R5 R6 R7
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2 7 TRUE TRUE 0.93 0.99 0.99 0.99 1
## 2 1 2 TRUE FALSE 0 0.99 0.99 0.98 1
## 3 10 1 TRUE FALSE 0 0.99 0.99 0.98 1
## 4 6 1 TRUE FALSE 0 0.02 0.7 0.36 0.55
##
## Tree shape (drivers annotated)
##
## \-GL
## \-2 [R3] :: PIK3CA, TP53, FBXW7, CDKN2A, SOX2, TERT, PRF1
## \-10 :: EP300
## \-1 :: NF1, CYLD
## \-6 :: FANCM
##
## Information transfer
##
## GL ---> PIK3CA
## GL ---> TP53
## GL ---> FBXW7
## GL ---> CDKN2A
## GL ---> SOX2
## GL ---> TERT
## GL ---> PRF1
## EP300 ---> NF1
## EP300 ---> CYLD
## PIK3CA ---> EP300
## TP53 ---> EP300
## FBXW7 ---> EP300
## CDKN2A ---> EP300
## SOX2 ---> EP300
## TERT ---> EP300
## PRF1 ---> EP300
## NF1 ---> FANCM
## CYLD ---> FANCM
##
## Tree score 0.125
##
## $phylogenies$CRUK0063$`2`
## [ ctree - ctree rank 2/6 for CRUK0063 ]
##
## # A tibble: 4 x 9
## cluster nMuts is.driver is.clonal R3 R4 R5 R6 R7
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2 7 TRUE TRUE 0.93 0.99 0.99 0.99 1
## 2 1 2 TRUE FALSE 0 0.99 0.99 0.98 1
## 3 10 1 TRUE FALSE 0 0.99 0.99 0.98 1
## 4 6 1 TRUE FALSE 0 0.02 0.7 0.36 0.55
##
## Tree shape (drivers annotated)
##
## \-GL
## \-2 [R3] :: PIK3CA, TP53, FBXW7, CDKN2A, SOX2, TERT, PRF1
## \-1 :: NF1, CYLD
## \-10 :: EP300
## \-6 :: FANCM
##
## Information transfer
##
## GL ---> PIK3CA
## GL ---> TP53
## GL ---> FBXW7
## GL ---> CDKN2A
## GL ---> SOX2
## GL ---> TERT
## GL ---> PRF1
## PIK3CA ---> NF1
## PIK3CA ---> CYLD
## TP53 ---> NF1
## TP53 ---> CYLD
## FBXW7 ---> NF1
## FBXW7 ---> CYLD
## CDKN2A ---> NF1
## CDKN2A ---> CYLD
## SOX2 ---> NF1
## SOX2 ---> CYLD
## TERT ---> NF1
## TERT ---> CYLD
## PRF1 ---> NF1
## PRF1 ---> CYLD
## NF1 ---> EP300
## CYLD ---> EP300
## EP300 ---> FANCM
##
## Tree score 0.125
##
## $phylogenies$CRUK0063$`3`
## [ ctree - ctree rank 3/6 for CRUK0063 ]
##
## # A tibble: 4 x 9
## cluster nMuts is.driver is.clonal R3 R4 R5 R6 R7
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2 7 TRUE TRUE 0.93 0.99 0.99 0.99 1
## 2 1 2 TRUE FALSE 0 0.99 0.99 0.98 1
## 3 10 1 TRUE FALSE 0 0.99 0.99 0.98 1
## 4 6 1 TRUE FALSE 0 0.02 0.7 0.36 0.55
##
## Tree shape (drivers annotated)
##
## \-GL
## \-2 [R3] :: PIK3CA, TP53, FBXW7, CDKN2A, SOX2, TERT, PRF1
## \-10 :: EP300
## |-1 :: NF1, CYLD
## \-6 :: FANCM
##
## Information transfer
##
## GL ---> PIK3CA
## GL ---> TP53
## GL ---> FBXW7
## GL ---> CDKN2A
## GL ---> SOX2
## GL ---> TERT
## GL ---> PRF1
## EP300 ---> NF1
## EP300 ---> CYLD
## PIK3CA ---> EP300
## TP53 ---> EP300
## FBXW7 ---> EP300
## CDKN2A ---> EP300
## SOX2 ---> EP300
## TERT ---> EP300
## PRF1 ---> EP300
## EP300 ---> FANCM
##
## Tree score 0.025
##
## $phylogenies$CRUK0063$`4`
## [ ctree - ctree rank 4/6 for CRUK0063 ]
##
## # A tibble: 4 x 9
## cluster nMuts is.driver is.clonal R3 R4 R5 R6 R7
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2 7 TRUE TRUE 0.93 0.99 0.99 0.99 1
## 2 1 2 TRUE FALSE 0 0.99 0.99 0.98 1
## 3 10 1 TRUE FALSE 0 0.99 0.99 0.98 1
## 4 6 1 TRUE FALSE 0 0.02 0.7 0.36 0.55
##
## Tree shape (drivers annotated)
##
## \-GL
## \-2 [R3] :: PIK3CA, TP53, FBXW7, CDKN2A, SOX2, TERT, PRF1
## \-1 :: NF1, CYLD
## |-10 :: EP300
## \-6 :: FANCM
##
## Information transfer
##
## GL ---> PIK3CA
## GL ---> TP53
## GL ---> FBXW7
## GL ---> CDKN2A
## GL ---> SOX2
## GL ---> TERT
## GL ---> PRF1
## PIK3CA ---> NF1
## PIK3CA ---> CYLD
## TP53 ---> NF1
## TP53 ---> CYLD
## FBXW7 ---> NF1
## FBXW7 ---> CYLD
## CDKN2A ---> NF1
## CDKN2A ---> CYLD
## SOX2 ---> NF1
## SOX2 ---> CYLD
## TERT ---> NF1
## TERT ---> CYLD
## PRF1 ---> NF1
## PRF1 ---> CYLD
## NF1 ---> EP300
## CYLD ---> EP300
## NF1 ---> FANCM
## CYLD ---> FANCM
##
## Tree score 0.025
##
## $phylogenies$CRUK0063$`5`
## [ ctree - ctree rank 5/6 for CRUK0063 ]
##
## # A tibble: 4 x 9
## cluster nMuts is.driver is.clonal R3 R4 R5 R6 R7
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2 7 TRUE TRUE 0.93 0.99 0.99 0.99 1
## 2 1 2 TRUE FALSE 0 0.99 0.99 0.98 1
## 3 10 1 TRUE FALSE 0 0.99 0.99 0.98 1
## 4 6 1 TRUE FALSE 0 0.02 0.7 0.36 0.55
##
## Tree shape (drivers annotated)
##
## \-GL
## \-2 [R3] :: PIK3CA, TP53, FBXW7, CDKN2A, SOX2, TERT, PRF1
## |-1 :: NF1, CYLD
## | \-6 :: FANCM
## \-10 :: EP300
##
## Information transfer
##
## GL ---> PIK3CA
## GL ---> TP53
## GL ---> FBXW7
## GL ---> CDKN2A
## GL ---> SOX2
## GL ---> TERT
## GL ---> PRF1
## PIK3CA ---> NF1
## PIK3CA ---> CYLD
## TP53 ---> NF1
## TP53 ---> CYLD
## FBXW7 ---> NF1
## FBXW7 ---> CYLD
## CDKN2A ---> NF1
## CDKN2A ---> CYLD
## SOX2 ---> NF1
## SOX2 ---> CYLD
## TERT ---> NF1
## TERT ---> CYLD
## PRF1 ---> NF1
## PRF1 ---> CYLD
## PIK3CA ---> EP300
## TP53 ---> EP300
## FBXW7 ---> EP300
## CDKN2A ---> EP300
## SOX2 ---> EP300
## TERT ---> EP300
## PRF1 ---> EP300
## NF1 ---> FANCM
## CYLD ---> FANCM
##
## Tree score 0.025
##
## $phylogenies$CRUK0063$`6`
## [ ctree - ctree rank 6/6 for CRUK0063 ]
##
## # A tibble: 4 x 9
## cluster nMuts is.driver is.clonal R3 R4 R5 R6 R7
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2 7 TRUE TRUE 0.93 0.99 0.99 0.99 1
## 2 1 2 TRUE FALSE 0 0.99 0.99 0.98 1
## 3 10 1 TRUE FALSE 0 0.99 0.99 0.98 1
## 4 6 1 TRUE FALSE 0 0.02 0.7 0.36 0.55
##
## Tree shape (drivers annotated)
##
## \-GL
## \-2 [R3] :: PIK3CA, TP53, FBXW7, CDKN2A, SOX2, TERT, PRF1
## |-10 :: EP300
## | \-6 :: FANCM
## \-1 :: NF1, CYLD
##
## Information transfer
##
## GL ---> PIK3CA
## GL ---> TP53
## GL ---> FBXW7
## GL ---> CDKN2A
## GL ---> SOX2
## GL ---> TERT
## GL ---> PRF1
## PIK3CA ---> NF1
## PIK3CA ---> CYLD
## TP53 ---> NF1
## TP53 ---> CYLD
## FBXW7 ---> NF1
## FBXW7 ---> CYLD
## CDKN2A ---> NF1
## CDKN2A ---> CYLD
## SOX2 ---> NF1
## SOX2 ---> CYLD
## TERT ---> NF1
## TERT ---> CYLD
## PRF1 ---> NF1
## PRF1 ---> CYLD
## PIK3CA ---> EP300
## TP53 ---> EP300
## FBXW7 ---> EP300
## CDKN2A ---> EP300
## SOX2 ---> EP300
## TERT ---> EP300
## PRF1 ---> EP300
## EP300 ---> FANCM
##
## Tree score 0.025
##
##
## $phylogenies$CRUK0064
## $phylogenies$CRUK0064$`1`
## [ ctree - ctree rank 1/1 for CRUK0064 ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 2 2 TRUE FALSE 0.64 0.11
## 2 1 1 TRUE TRUE 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53
## \-2 :: MLH1, FAT1
##
## Information transfer
##
## TP53 ---> MLH1
## TP53 ---> FAT1
## GL ---> TP53
##
## Tree score 1
##
##
## $phylogenies$CRUK0065
## $phylogenies$CRUK0065$`1`
## [ ctree - ctree rank 1/1 for CRUK0065 ]
##
## # A tibble: 3 x 10
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5 R6
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 0.99 0.99 1 1 1
## 2 2 3 TRUE FALSE 0 0 0 0 0.48 0
## 3 6 2 TRUE FALSE 0 0 0 0 0.01 0.83
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: TP53, NFE2L2, PIK3CA, SOX2
## |-2 :: MLH1, PTPRC, UBR5
## \-6 :: NOTCH1, NCOA6
##
## Information transfer
##
## GL ---> TP53
## GL ---> NFE2L2
## GL ---> PIK3CA
## GL ---> SOX2
## TP53 ---> MLH1
## TP53 ---> PTPRC
## TP53 ---> UBR5
## NFE2L2 ---> MLH1
## NFE2L2 ---> PTPRC
## NFE2L2 ---> UBR5
## PIK3CA ---> MLH1
## PIK3CA ---> PTPRC
## PIK3CA ---> UBR5
## SOX2 ---> MLH1
## SOX2 ---> PTPRC
## SOX2 ---> UBR5
## TP53 ---> NOTCH1
## TP53 ---> NCOA6
## NFE2L2 ---> NOTCH1
## NFE2L2 ---> NCOA6
## PIK3CA ---> NOTCH1
## PIK3CA ---> NCOA6
## SOX2 ---> NOTCH1
## SOX2 ---> NCOA6
##
## Tree score 1
##
##
## $phylogenies$CRUK0066
## $phylogenies$CRUK0066$`1`
## [ ctree - ctree rank 1/1 for CRUK0066 ]
##
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 7 TRUE TRUE 0.99 1 1 0.99
## 2 9 1 TRUE FALSE 0 0.91 0.01 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R4] :: TP53, NOTCH1, CDKN2A, WRN, PDGFRA, TERT, NCOA6
## \-9 :: COL5A2
##
## Information transfer
##
## GL ---> TP53
## GL ---> NOTCH1
## GL ---> CDKN2A
## GL ---> WRN
## GL ---> PDGFRA
## GL ---> TERT
## GL ---> NCOA6
## TP53 ---> COL5A2
## NOTCH1 ---> COL5A2
## CDKN2A ---> COL5A2
## WRN ---> COL5A2
## PDGFRA ---> COL5A2
## TERT ---> COL5A2
## NCOA6 ---> COL5A2
##
## Tree score 1
##
##
## $phylogenies$CRUK0067
## $phylogenies$CRUK0067$`1`
## [ ctree - ctree rank 1/1 for CRUK0067 ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 0.99 1
## 2 2 1 TRUE FALSE 0.61 0.83
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: NOTCH1, TP53, PIK3CA, SOX2, CDKN2A
## \-2 :: NFE2L2
##
## Information transfer
##
## GL ---> NOTCH1
## GL ---> TP53
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> CDKN2A
## NOTCH1 ---> NFE2L2
## TP53 ---> NFE2L2
## PIK3CA ---> NFE2L2
## SOX2 ---> NFE2L2
## CDKN2A ---> NFE2L2
##
## Tree score 1
##
##
## $phylogenies$CRUK0068
## $phylogenies$CRUK0068$`1`
## [ ctree - ctree rank 1/1 for CRUK0068 ]
##
## # A tibble: 4 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 0.99 1 1 1
## 2 3 1 TRUE FALSE 0.5 0 0 0
## 3 4 1 TRUE FALSE 0.98 0.37 0.99 0.01
## 4 9 1 TRUE FALSE 0 0 0 0.69
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53, PTEN, KMT2D, PIK3CA, SOX2
## |-4 :: SETD2
## | \-3 :: MGA
## \-9 :: TERT
##
## Information transfer
##
## GL ---> TP53
## GL ---> PTEN
## GL ---> KMT2D
## GL ---> PIK3CA
## GL ---> SOX2
## SETD2 ---> MGA
## TP53 ---> SETD2
## PTEN ---> SETD2
## KMT2D ---> SETD2
## PIK3CA ---> SETD2
## SOX2 ---> SETD2
## TP53 ---> TERT
## PTEN ---> TERT
## KMT2D ---> TERT
## PIK3CA ---> TERT
## SOX2 ---> TERT
##
## Tree score 1
##
##
## $phylogenies$CRUK0069
## $phylogenies$CRUK0069$`1`
## [ ctree - ctree rank 1/1 for CRUK0069 ]
##
## # A tibble: 2 x 9
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1 1
## 2 13 1 TRUE FALSE 0.93 0.42 0.32 0.94 0.96
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53, FAT1, PDGFRA, FGFR1
## \-13 :: KRAS
##
## Information transfer
##
## GL ---> TP53
## GL ---> FAT1
## GL ---> PDGFRA
## GL ---> FGFR1
## TP53 ---> KRAS
## FAT1 ---> KRAS
## PDGFRA ---> KRAS
## FGFR1 ---> KRAS
##
## Tree score 1
##
##
## $phylogenies$CRUK0070
## $phylogenies$CRUK0070$`1`
## [ ctree - ctree rank 1/1 for CRUK0070 ]
##
## # A tibble: 3 x 9
## cluster nMuts is.driver is.clonal R1 R2 R4 R6 R7
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1 1
## 2 2 1 TRUE FALSE 0 0 0 0.95 0.98
## 3 3 1 TRUE FALSE 0.95 0.96 0.98 0 0.01
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: DNM2, TP53, COL5A2, SOX2
## |-3 :: NFE2L2
## \-2 :: CBLB
##
## Information transfer
##
## GL ---> DNM2
## GL ---> TP53
## GL ---> COL5A2
## GL ---> SOX2
## DNM2 ---> CBLB
## TP53 ---> CBLB
## COL5A2 ---> CBLB
## SOX2 ---> CBLB
## DNM2 ---> NFE2L2
## TP53 ---> NFE2L2
## COL5A2 ---> NFE2L2
## SOX2 ---> NFE2L2
##
## Tree score 1
##
##
## $phylogenies$CRUK0071
## $phylogenies$CRUK0071$`1`
## [ ctree - ctree rank 1/1 for CRUK0071 ]
##
## # A tibble: 2 x 10
## cluster nMuts is.driver is.clonal R1 R2 R3 R5 R6 R7
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 1 0.99 1 1 1 1
## 2 4 1 TRUE FALSE 0 0.570 0 0 0 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R3, R5, R6, R7] :: CMTR2, PIK3CA, SOX2
## \-4 :: UBR5
##
## Information transfer
##
## GL ---> CMTR2
## GL ---> PIK3CA
## GL ---> SOX2
## CMTR2 ---> UBR5
## PIK3CA ---> UBR5
## SOX2 ---> UBR5
##
## Tree score 1
##
##
## $phylogenies$CRUK0072
## $phylogenies$CRUK0072$`1`
## [ ctree - ctree rank 1/1 for CRUK0072 ]
##
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 1 0.99 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R4] :: TP53, NFE2L2, PIK3CA, SOX2, EGFR, MYC
##
## Information transfer
##
## GL ---> TP53
## GL ---> NFE2L2
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> EGFR
## GL ---> MYC
##
## Tree score 1
##
##
## $phylogenies$CRUK0073
## $phylogenies$CRUK0073$`1`
## [ ctree - ctree rank 1/1 for CRUK0073 ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 8 TRUE TRUE 1 1
## 2 2 1 TRUE FALSE 0 0.93
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1] :: CDKN2A, DICER1, NFE2L2, FAT1, KMT2D, NOTCH2, FGFR1, MYC
## \-2 :: PLXNB2
##
## Information transfer
##
## GL ---> CDKN2A
## GL ---> DICER1
## GL ---> NFE2L2
## GL ---> FAT1
## GL ---> KMT2D
## GL ---> NOTCH2
## GL ---> FGFR1
## GL ---> MYC
## CDKN2A ---> PLXNB2
## DICER1 ---> PLXNB2
## NFE2L2 ---> PLXNB2
## FAT1 ---> PLXNB2
## KMT2D ---> PLXNB2
## NOTCH2 ---> PLXNB2
## FGFR1 ---> PLXNB2
## MYC ---> PLXNB2
##
## Tree score 1
##
##
## $phylogenies$CRUK0074
## $phylogenies$CRUK0074$`1`
## [ ctree - ctree rank 1/1 for CRUK0074 ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 0.99 1
## 2 3 1 TRUE FALSE 0 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1] :: TP53, NFE2L2, PIK3CA, SOX2, CCND1
## \-3 :: UBR5
##
## Information transfer
##
## GL ---> TP53
## GL ---> NFE2L2
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> CCND1
## TP53 ---> UBR5
## NFE2L2 ---> UBR5
## PIK3CA ---> UBR5
## SOX2 ---> UBR5
## CCND1 ---> UBR5
##
## Tree score 1
##
##
## $phylogenies$CRUK0075
## $phylogenies$CRUK0075$`1`
## [ ctree - ctree rank 1/1 for CRUK0075 ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 7 TRUE TRUE 1 0.99
## 2 2 1 TRUE FALSE 0.15 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: NOTCH1, RASA1, TP53, FAT1, MGA, PIK3CA, FGFR1
## \-2 :: NFE2L2
##
## Information transfer
##
## GL ---> NOTCH1
## GL ---> RASA1
## GL ---> TP53
## GL ---> FAT1
## GL ---> MGA
## GL ---> PIK3CA
## GL ---> FGFR1
## NOTCH1 ---> NFE2L2
## RASA1 ---> NFE2L2
## TP53 ---> NFE2L2
## FAT1 ---> NFE2L2
## MGA ---> NFE2L2
## PIK3CA ---> NFE2L2
## FGFR1 ---> NFE2L2
##
## Tree score 1
##
##
## $phylogenies$CRUK0076
## $phylogenies$CRUK0076$`1`
## [ ctree - ctree rank 1/3 for CRUK0076 ]
##
## # A tibble: 3 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 1 1 1 1
## 2 2 1 TRUE FALSE 0.93 0 0.28 0
## 3 3 1 TRUE FALSE 0.93 0 0.81 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R2, R4] :: SERPINB13, TP53, ARID1B, PIK3CA, SOX2, FGFR1
## \-3 :: COL5A2
## \-2 :: NCOR1
##
## Information transfer
##
## GL ---> SERPINB13
## GL ---> TP53
## GL ---> ARID1B
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> FGFR1
## COL5A2 ---> NCOR1
## SERPINB13 ---> COL5A2
## TP53 ---> COL5A2
## ARID1B ---> COL5A2
## PIK3CA ---> COL5A2
## SOX2 ---> COL5A2
## FGFR1 ---> COL5A2
##
## Tree score 0.444444444444444
##
## $phylogenies$CRUK0076$`2`
## [ ctree - ctree rank 2/3 for CRUK0076 ]
##
## # A tibble: 3 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 1 1 1 1
## 2 2 1 TRUE FALSE 0.93 0 0.28 0
## 3 3 1 TRUE FALSE 0.93 0 0.81 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R2, R4] :: SERPINB13, TP53, ARID1B, PIK3CA, SOX2, FGFR1
## |-2 :: NCOR1
## \-3 :: COL5A2
##
## Information transfer
##
## GL ---> SERPINB13
## GL ---> TP53
## GL ---> ARID1B
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> FGFR1
## SERPINB13 ---> NCOR1
## TP53 ---> NCOR1
## ARID1B ---> NCOR1
## PIK3CA ---> NCOR1
## SOX2 ---> NCOR1
## FGFR1 ---> NCOR1
## SERPINB13 ---> COL5A2
## TP53 ---> COL5A2
## ARID1B ---> COL5A2
## PIK3CA ---> COL5A2
## SOX2 ---> COL5A2
## FGFR1 ---> COL5A2
##
## Tree score 0.111111111111111
##
## $phylogenies$CRUK0076$`3`
## [ ctree - ctree rank 3/3 for CRUK0076 ]
##
## # A tibble: 3 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 1 1 1 1
## 2 2 1 TRUE FALSE 0.93 0 0.28 0
## 3 3 1 TRUE FALSE 0.93 0 0.81 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R2, R4] :: SERPINB13, TP53, ARID1B, PIK3CA, SOX2, FGFR1
## \-2 :: NCOR1
## \-3 :: COL5A2
##
## Information transfer
##
## GL ---> SERPINB13
## GL ---> TP53
## GL ---> ARID1B
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> FGFR1
## SERPINB13 ---> NCOR1
## TP53 ---> NCOR1
## ARID1B ---> NCOR1
## PIK3CA ---> NCOR1
## SOX2 ---> NCOR1
## FGFR1 ---> NCOR1
## NCOR1 ---> COL5A2
##
## Tree score 0.0833333333333333
##
##
## $phylogenies$CRUK0077
## $phylogenies$CRUK0077$`1`
## [ ctree - ctree rank 1/1 for CRUK0077 ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 1 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: TP53, LATS1, KEAP1
##
## Information transfer
##
## GL ---> TP53
## GL ---> LATS1
## GL ---> KEAP1
##
## Tree score 1
##
##
## $phylogenies$CRUK0078
## $phylogenies$CRUK0078$`1`
## [ ctree - ctree rank 1/1 for CRUK0078 ]
##
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R2, R3, R4] :: PLXNB2, PTEN, PIK3CA, SOX2, FGFR1
##
## Information transfer
##
## GL ---> PLXNB2
## GL ---> PTEN
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> FGFR1
##
## Tree score 1
##
##
## $phylogenies$CRUK0079
## $phylogenies$CRUK0079$`1`
## [ ctree - ctree rank 1/1 for CRUK0079 ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 1 0.99 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: FAT1, TP53, POLE, PIK3CA, SOX2, FGFR1
##
## Information transfer
##
## GL ---> FAT1
## GL ---> TP53
## GL ---> POLE
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> FGFR1
##
## Tree score 1
##
##
## $phylogenies$CRUK0080
## $phylogenies$CRUK0080$`1`
## [ ctree - ctree rank 1/1 for CRUK0080 ]
##
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal R3 R4 R5 R6
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1
## 2 3 1 TRUE FALSE 0 0 0.97 0.83
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R3, R4] :: TP53, WT1, EGFR, CCND1
## \-3 :: IKZF1
##
## Information transfer
##
## GL ---> TP53
## GL ---> WT1
## GL ---> EGFR
## GL ---> CCND1
## TP53 ---> IKZF1
## WT1 ---> IKZF1
## EGFR ---> IKZF1
## CCND1 ---> IKZF1
##
## Tree score 1
##
##
## $phylogenies$CRUK0081
## $phylogenies$CRUK0081$`1`
## [ ctree - ctree rank 1/1 for CRUK0081 ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R5
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 1 0.99
## 2 3 1 TRUE FALSE 0.93 0.01
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: NOTCH1, TP53, CDKN2A, FAT1, FANCC
## \-3 :: CYLD
##
## Information transfer
##
## GL ---> NOTCH1
## GL ---> TP53
## GL ---> CDKN2A
## GL ---> FAT1
## GL ---> FANCC
## NOTCH1 ---> CYLD
## TP53 ---> CYLD
## CDKN2A ---> CYLD
## FAT1 ---> CYLD
## FANCC ---> CYLD
##
## Tree score 1
##
##
## $phylogenies$CRUK0082
## $phylogenies$CRUK0082$`1`
## [ ctree - ctree rank 1/1 for CRUK0082 ]
##
## # A tibble: 1 x 9
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 8 TRUE TRUE 1 1 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4, R5] :: TP53, WT1, PTEN, COL5A2, KMT2D, PIK3CA, SOX2, FGFR1
##
## Information transfer
##
## GL ---> TP53
## GL ---> WT1
## GL ---> PTEN
## GL ---> COL5A2
## GL ---> KMT2D
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> FGFR1
##
## Tree score 1
##
##
## $phylogenies$CRUK0083
## $phylogenies$CRUK0083$`1`
## [ ctree - ctree rank 1/1 for CRUK0083 ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 7 TRUE TRUE 1 1 1 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: TP53, FBXW7, RASA1, PIK3CA, SOX2, FGFR1, MYC
##
## Information transfer
##
## GL ---> TP53
## GL ---> FBXW7
## GL ---> RASA1
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> FGFR1
## GL ---> MYC
##
## Tree score 1
##
##
## $phylogenies$CRUK0084
## $phylogenies$CRUK0084$`1`
## [ ctree - ctree rank 1/1 for CRUK0084 ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 1 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: CREBBP
##
## Information transfer
##
## GL ---> CREBBP
##
## Tree score 1
##
##
## $phylogenies$CRUK0085
## $phylogenies$CRUK0085$`1`
## [ ctree - ctree rank 1/1 for CRUK0085 ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: CHEK2, CREBBP, LATS1, FANCM
##
## Information transfer
##
## GL ---> CHEK2
## GL ---> CREBBP
## GL ---> LATS1
## GL ---> FANCM
##
## Tree score 1
##
##
## $phylogenies$CRUK0086
## $phylogenies$CRUK0086$`1`
## [ ctree - ctree rank 1/1 for CRUK0086 ]
##
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R4] :: TP53, ARID2, FAT1
##
## Information transfer
##
## GL ---> TP53
## GL ---> ARID2
## GL ---> FAT1
##
## Tree score 1
##
##
## $phylogenies$CRUK0087
## $phylogenies$CRUK0087$`1`
## [ ctree - ctree rank 1/1 for CRUK0087 ]
##
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3] :: NFE2L2, TP53, ASXL1, PIK3CA
##
## Information transfer
##
## GL ---> NFE2L2
## GL ---> TP53
## GL ---> ASXL1
## GL ---> PIK3CA
##
## Tree score 1
##
##
## $phylogenies$CRUK0088
## $phylogenies$CRUK0088$`1`
## [ ctree - ctree rank 1/1 for CRUK0088 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: CUX1, TP53
##
## Information transfer
##
## GL ---> CUX1
## GL ---> TP53
##
## Tree score 1
##
##
## $phylogenies$CRUK0089
## $phylogenies$CRUK0089$`1`
## [ ctree - ctree rank 1/1 for CRUK0089 ]
##
## # A tibble: 1 x 5
## cluster nMuts is.driver is.clonal R2
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 3 TRUE TRUE 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R2] :: PIK3CA, SMAD4, KEAP1
##
## Information transfer
##
## GL ---> PIK3CA
## GL ---> SMAD4
## GL ---> KEAP1
##
## Tree score 1
##
##
## $phylogenies$CRUK0090
## $phylogenies$CRUK0090$`1`
## [ ctree - ctree rank 1/1 for CRUK0090 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: CDKN2A, NCOA6, CUX1, COL2A1, NRAS
##
## Information transfer
##
## GL ---> CDKN2A
## GL ---> NCOA6
## GL ---> CUX1
## GL ---> COL2A1
## GL ---> NRAS
##
## Tree score 1
##
##
## $phylogenies$CRUK0091
## $phylogenies$CRUK0091$`1`
## [ ctree - ctree rank 1/1 for CRUK0091 ]
##
## # A tibble: 1 x 5
## cluster nMuts is.driver is.clonal R2
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 3 TRUE TRUE 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R2] :: TP53, SMARCA4, CDKN2A
##
## Information transfer
##
## GL ---> TP53
## GL ---> SMARCA4
## GL ---> CDKN2A
##
## Tree score 1
##
##
## $phylogenies$CRUK0092
## $phylogenies$CRUK0092$`1`
## [ ctree - ctree rank 1/1 for CRUK0092 ]
##
## # A tibble: 1 x 5
## cluster nMuts is.driver is.clonal R1
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 5 TRUE TRUE 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1] :: TP53, SMAD4, RASA1, CBLB, PIK3CA
##
## Information transfer
##
## GL ---> TP53
## GL ---> SMAD4
## GL ---> RASA1
## GL ---> CBLB
## GL ---> PIK3CA
##
## Tree score 1
##
##
## $phylogenies$CRUK0093
## $phylogenies$CRUK0093$`1`
## [ ctree - ctree rank 1/1 for CRUK0093 ]
##
## # A tibble: 1 x 5
## cluster nMuts is.driver is.clonal R1
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 7 TRUE TRUE 0.96
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1] :: DICER1, CDKN2A, COL2A1, GATA3, CIC, COL5A2, TP53
##
## Information transfer
##
## GL ---> DICER1
## GL ---> CDKN2A
## GL ---> COL2A1
## GL ---> GATA3
## GL ---> CIC
## GL ---> COL5A2
## GL ---> TP53
##
## Tree score 1
##
##
## $phylogenies$CRUK0094
## $phylogenies$CRUK0094$`1`
## [ ctree - ctree rank 1/1 for CRUK0094 ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.98 0.98 0.97 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: SMARCA4, TERT
##
## Information transfer
##
## GL ---> SMARCA4
## GL ---> TERT
##
## Tree score 1
##
##
## $phylogenies$CRUK0095
## $phylogenies$CRUK0095$`1`
## [ ctree - ctree rank 1/1 for CRUK0095 ]
##
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.99 0.99 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3] :: TP53, NF1, RASA1
##
## Information transfer
##
## GL ---> TP53
## GL ---> NF1
## GL ---> RASA1
##
## Tree score 1
##
##
## $phylogenies$CRUK0096
## $phylogenies$CRUK0096$`1`
## [ ctree - ctree rank 1/1 for CRUK0096 ]
##
## # A tibble: 1 x 11
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5 R6
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 1 1 1 1 1 1
## # … with 1 more variable: R7 <dbl>
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4, R5, R6, R7] :: KRAS, SGK223, MAP3K1
##
## Information transfer
##
## GL ---> KRAS
## GL ---> SGK223
## GL ---> MAP3K1
##
## Tree score 1
##
##
## $phylogenies$CRUK0097
## $phylogenies$CRUK0097$`1`
## [ ctree - ctree rank 1/1 for CRUK0097 ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.995 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: TP53, PTEN
##
## Information transfer
##
## GL ---> TP53
## GL ---> PTEN
##
## Tree score 1
##
##
## $phylogenies$CRUK0098
## $phylogenies$CRUK0098$`1`
## [ ctree - ctree rank 1/1 for CRUK0098 ]
##
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 1 1 1
## 2 3 1 TRUE FALSE 0.96 0.91 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R3] :: TP53, PTEN
## \-3 :: UBR5
##
## Information transfer
##
## GL ---> TP53
## GL ---> PTEN
## TP53 ---> UBR5
## PTEN ---> UBR5
##
## Tree score 1
##
##
## $phylogenies$CRUK0099
## $phylogenies$CRUK0099$`1`
## [ ctree - ctree rank 1/1 for CRUK0099 ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R3 R6 R7
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.95 0.97 0.91 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R3, R6, R7] :: STK11, KEAP1, TP53
##
## Information transfer
##
## GL ---> STK11
## GL ---> KEAP1
## GL ---> TP53
##
## Tree score 1
##
##
## $phylogenies$CRUK0100
## $phylogenies$CRUK0100$`1`
## [ ctree - ctree rank 1/1 for CRUK0100 ]
##
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3] :: TP53, PHOX2B, COL5A2, STK11, SPEN, CDKN2A
##
## Information transfer
##
## GL ---> TP53
## GL ---> PHOX2B
## GL ---> COL5A2
## GL ---> STK11
## GL ---> SPEN
## GL ---> CDKN2A
##
## Tree score 1
##
##
##
## $fit
## $fit$fit_table
## # A tibble: 99 x 9
## patientID hasTrees numTrees maxScore minScore combInfTransf Solution
## <chr> <lgl> <int> <dbl> <dbl> <int> <int>
## 1 CRUK0001 TRUE 3 0.111 0.111 3 1
## 2 CRUK0002 TRUE 2 0.75 0.0833 2 1
## 3 CRUK0003 TRUE 1 1 1 1 1
## 4 CRUK0004 TRUE 1 1 1 1 1
## 5 CRUK0005 TRUE 1 1 1 1 1
## 6 CRUK0006 TRUE 2 0.667 0.167 2 1
## 7 CRUK0007 TRUE 1 1 1 1 1
## 8 CRUK0008 TRUE 1 1 1 1 1
## 9 CRUK0009 TRUE 1 1 1 1 1
## 10 CRUK0010 TRUE 1 1 1 1 1
## # … with 89 more rows, and 2 more variables: converged <lgl>,
## # penalty <dbl>
##
## $fit$penalty
## # A tibble: 262 x 4
## from to count penalty
## <chr> <chr> <int> <dbl>
## 1 ARHGAP35 TERT 2 0.08
## 2 ARID1B ASXL1 1 0.333
## 3 ARID1B COL5A2 1 0.0455
## 4 ARID1B KRAS 1 0.0222
## 5 ARID2 KRAS 2 0.0444
## 6 ATM CCND1 1 0.125
## 7 ATM MGA 1 0.1
## 8 ATM NCOR1 1 0.125
## 9 BAP1 PIK3CA 1 0.0476
## 10 BAP1 RB1 1 0.2
## # … with 252 more rows
##
## $fit$phylogenies
## $fit$phylogenies$CRUK0001
## [ ctree - ctree rank 1/3 for CRUK0001 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 4 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 3 4 TRUE TRUE 0.99 0.99 1
## 2 1 1 TRUE FALSE 0.86 0 0
## 3 2 1 TRUE FALSE 0.19 0 0.95
## 4 5 1 TRUE FALSE 0.82 0 0.71
##
## Tree shape (drivers annotated)
##
## \-GL
## \-3 [R2] :: TP53, MGA, WRN, EGFR
## |-1 :: NF1
## | \-5 :: PASK
## \-2 :: ARHGAP35
##
## Information transfer
##
## GL ---> EGFR
## GL ---> WRN
## GL ---> MGA
## EGFR ---> TP53
## WRN ---> TP53
## TP53 ---> NF1
## MGA ---> NF1
## TP53 ---> ARHGAP35
## MGA ---> ARHGAP35
## NF1 ---> PASK
##
## Tree score 0.111111111111111
##
## $fit$phylogenies$CRUK0002
## [ ctree - ctree rank 1/2 for CRUK0002 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 4 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE FALSE 0 0.92 0
## 2 2 2 TRUE TRUE 0.99 0.98 0.99
## 3 5 1 TRUE FALSE 0.78 0 0
## 4 6 1 TRUE FALSE 0.96 0.03 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-2 :: MET, TERT
## |-6 :: EP300
## | \-5 :: NF1
## \-1 :: RB1, IKZF1, KRAS
##
## Information transfer
##
## GL ---> MET
## MET ---> TERT
## TERT ---> EP300
## TERT ---> RB1
## TERT ---> IKZF1
## TERT ---> KRAS
## EP300 ---> NF1
##
## Tree score 0.75
##
## $fit$phylogenies$CRUK0003
## [ ctree - ctree rank 1/1 for CRUK0003 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 9
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R6
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.98 0.97 0.87 0.97 0.99
## 2 4 1 TRUE FALSE 0 0 0.49 0 0.01
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R4] :: PIK3CA, EGFR, CDKN2A
## \-4 :: CTNNB1
##
## Information transfer
##
## GL ---> PIK3CA
## GL ---> EGFR
## GL ---> CDKN2A
## PIK3CA ---> CTNNB1
## EGFR ---> CTNNB1
## CDKN2A ---> CTNNB1
##
## Tree score 1
##
## $fit$phylogenies$CRUK0004
## [ ctree - ctree rank 1/1 for CRUK0004 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 2 TRUE FALSE 0 0 0.95 0.01
## 2 2 2 TRUE TRUE 0.99 0.985 0.99 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-2 [R1, R2] :: TP53, EGFR
## \-1 :: SMAD4, NOTCH1
##
## Information transfer
##
## GL ---> EGFR
## EGFR ---> TP53
## TP53 ---> SMAD4
## TP53 ---> NOTCH1
##
## Tree score 1
##
## $fit$phylogenies$CRUK0005
## [ ctree - ctree rank 1/1 for CRUK0005 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 2 5 TRUE TRUE 1 1 0.97 1
## 2 1 1 TRUE FALSE 0 0 0.8 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-2 [R1, R2, R4] :: CMTR2, TP53, BRAF, PASK, TERT
## \-1 :: NRAS
##
## Information transfer
##
## GL ---> BRAF
## GL ---> TP53
## GL ---> CMTR2
## GL ---> PASK
## BRAF ---> TERT
## TP53 ---> TERT
## CMTR2 ---> NRAS
## PASK ---> NRAS
## TERT ---> NRAS
##
## Tree score 1
##
## $fit$phylogenies$CRUK0006
## [ ctree - ctree rank 1/2 for CRUK0006 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 3 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1
## 2 2 1 TRUE FALSE 0 0.93
## 3 7 1 TRUE FALSE 0.99 0.06
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: PLXNB2, TP53, KEAP1, TERT
## |-7 :: FANCC
## \-2 :: MAP3K1
##
## Information transfer
##
## GL ---> TP53
## GL ---> KEAP1
## TP53 ---> PLXNB2
## TP53 ---> TERT
## PLXNB2 ---> MAP3K1
## KEAP1 ---> MAP3K1
## TERT ---> MAP3K1
## PLXNB2 ---> FANCC
## KEAP1 ---> FANCC
## TERT ---> FANCC
##
## Tree score 0.666666666666667
##
## $fit$phylogenies$CRUK0007
## [ ctree - ctree rank 1/1 for CRUK0007 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.98 0.93
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: PIK3CA, EGFR, SGK223
##
## Information transfer
##
## GL ---> PIK3CA
## GL ---> EGFR
## GL ---> SGK223
##
## Tree score 1
##
## $fit$phylogenies$CRUK0008
## [ ctree - ctree rank 1/1 for CRUK0008 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 2 5 TRUE TRUE 0.99 1
## 2 3 1 TRUE FALSE 0.86 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-2 [R2] :: KEAP1, STK11, PRDM1, U2AF1, MYC
## \-3 :: ARID2
##
## Information transfer
##
## GL ---> KEAP1
## GL ---> STK11
## GL ---> PRDM1
## GL ---> U2AF1
## GL ---> MYC
## KEAP1 ---> ARID2
## STK11 ---> ARID2
## PRDM1 ---> ARID2
## U2AF1 ---> ARID2
## MYC ---> ARID2
##
## Tree score 1
##
## $fit$phylogenies$CRUK0009
## [ ctree - ctree rank 1/1 for CRUK0009 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 0.99 0.99 0.98 0.99
## 2 2 1 TRUE FALSE 0 0.93 0 0.96
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R3] :: BRAF, TP53, ARHGAP35, KMT2C, NFE2L2, MET
## \-2 :: TERT
##
## Information transfer
##
## GL ---> TP53
## GL ---> BRAF
## GL ---> KMT2C
## GL ---> MET
## TP53 ---> ARHGAP35
## TP53 ---> NFE2L2
## BRAF ---> TERT
## ARHGAP35 ---> TERT
## KMT2C ---> TERT
## NFE2L2 ---> TERT
## MET ---> TERT
##
## Tree score 1
##
## $fit$phylogenies$CRUK0010
## [ ctree - ctree rank 1/1 for CRUK0010 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.95 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: SETD2, EGFR, TERT
##
## Information transfer
##
## GL ---> SETD2
## GL ---> EGFR
## GL ---> TERT
##
## Tree score 1
##
## $fit$phylogenies$CRUK0011
## [ ctree - ctree rank 1/1 for CRUK0011 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.97 1
## 2 3 1 TRUE FALSE 0.95 0 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R2, R3] :: KRAS
## \-3 :: FLT4
##
## Information transfer
##
## GL ---> KRAS
## KRAS ---> FLT4
##
## Tree score 1
##
## $fit$phylogenies$CRUK0012
## [ ctree - ctree rank 1/1 for CRUK0012 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.98 0.95
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: EGFR
##
## Information transfer
##
## GL ---> EGFR
##
## Tree score 1
##
## $fit$phylogenies$CRUK0013
## [ ctree - ctree rank 1/4 for CRUK0013 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 4 x 9
## cluster nMuts is.driver is.clonal LN1 LN2 R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.99 0.99 0.99 0.99
## 2 2 1 TRUE FALSE 0 0 0 0.75 0
## 3 3 1 TRUE FALSE 0.97 0.96 0.01 0.580 0.94
## 4 4 1 TRUE FALSE 0 0 0.97 0.37 0.01
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: STK11
## |-3 :: KRAS
## |-4 :: EGFR
## \-2 :: NOTCH1
##
## Information transfer
##
## GL ---> STK11
## STK11 ---> NOTCH1
## STK11 ---> KRAS
## STK11 ---> EGFR
##
## Tree score 0.3
##
## $fit$phylogenies$CRUK0014
## [ ctree - ctree rank 1/1 for CRUK0014 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.96 0.96
## 2 2 1 TRUE FALSE 0.35 0.01
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53, KRAS
## \-2 :: RNF43
##
## Information transfer
##
## GL ---> KRAS
## GL ---> TP53
## KRAS ---> TP53
## TP53 ---> KRAS
## KRAS ---> RNF43
## TP53 ---> RNF43
##
## Tree score 1
##
## $fit$phylogenies$CRUK0015
## [ ctree - ctree rank 1/1 for CRUK0015 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 3 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.99 0.99
## 2 2 1 TRUE FALSE 0.94 0.01
## 3 3 1 TRUE FALSE 0.01 0.65
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: BAP1, EGFR
## |-2 :: TP53
## \-3 :: RB1
##
## Information transfer
##
## GL ---> BAP1
## GL ---> EGFR
## BAP1 ---> TP53
## EGFR ---> TP53
## BAP1 ---> RB1
## EGFR ---> RB1
##
## Tree score 1
##
## $fit$phylogenies$CRUK0016
## [ ctree - ctree rank 1/13 for CRUK0016 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 5 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 0.99 0.99
## 2 16 2 TRUE FALSE 0.97 0
## 3 10 1 TRUE FALSE 0.34 0.3
## 4 2 1 TRUE FALSE 0.53 0
## 5 6 1 TRUE FALSE 0.31 0.53
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53, FAT1, SPEN, CBLB, TERT, CDKN2A
## |-16 :: LATS1, ARID1B
## | \-2 :: ASXL1
## |-10 :: DNM2
## \-6 :: PTPRC
##
## Information transfer
##
## GL ---> CDKN2A
## GL ---> SPEN
## CDKN2A ---> TP53
## TP53 ---> FAT1
## TP53 ---> CBLB
## TP53 ---> TERT
## FAT1 ---> LATS1
## SPEN ---> LATS1
## CBLB ---> LATS1
## TERT ---> LATS1
## FAT1 ---> ARID1B
## SPEN ---> ARID1B
## CBLB ---> ARID1B
## TERT ---> ARID1B
## FAT1 ---> DNM2
## SPEN ---> DNM2
## CBLB ---> DNM2
## TERT ---> DNM2
## FAT1 ---> PTPRC
## SPEN ---> PTPRC
## CBLB ---> PTPRC
## TERT ---> PTPRC
## LATS1 ---> ASXL1
## ARID1B ---> ASXL1
##
## Tree score 0.03125
##
## $fit$phylogenies$CRUK0017
## [ ctree - ctree rank 1/1 for CRUK0017 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 1 1 1 1
## 2 3 1 TRUE FALSE 0 0.94 0.95 0.59
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1] :: TP53, ARID1B, ARID2, KEAP1, MYC
## \-3 :: KRAS
##
## Information transfer
##
## GL ---> KEAP1
## GL ---> MYC
## GL ---> TP53
## KEAP1 ---> ARID2
## MYC ---> ARID2
## TP53 ---> ARID1B
## ARID1B ---> KRAS
## ARID2 ---> KRAS
##
## Tree score 1
##
## $fit$phylogenies$CRUK0018
## [ ctree - ctree rank 1/1 for CRUK0018 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: CMTR2, KRAS, MGA, COL5A2
##
## Information transfer
##
## GL ---> KRAS
## GL ---> CMTR2
## GL ---> COL5A2
## KRAS ---> MGA
##
## Tree score 1
##
## $fit$phylogenies$CRUK0019
## [ ctree - ctree rank 1/1 for CRUK0019 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.97 0.96
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: EGFR
##
## Information transfer
##
## GL ---> EGFR
##
## Tree score 1
##
## $fit$phylogenies$CRUK0020
## [ ctree - ctree rank 1/2 for CRUK0020 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 4 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 7 TRUE TRUE 1 1
## 2 2 1 TRUE FALSE 0.87 0
## 3 3 1 TRUE FALSE 0.9 0.08
## 4 4 1 TRUE FALSE 0 0.85
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: KEAP1, TP53, MGA, ARID2, COL2A1, PRF1, KRAS
## |-3 :: BAP1
## | \-2 :: PIK3CA
## \-4 :: NCOR1
##
## Information transfer
##
## GL ---> KEAP1
## GL ---> COL2A1
## GL ---> PRF1
## GL ---> KRAS
## GL ---> TP53
## ARID2 ---> KRAS
## KEAP1 ---> ARID2
## KEAP1 ---> KRAS
## KRAS ---> TP53
## KRAS ---> MGA
## TP53 ---> KRAS
## MGA ---> BAP1
## COL2A1 ---> BAP1
## PRF1 ---> BAP1
## KRAS ---> BAP1
## TP53 ---> BAP1
## MGA ---> NCOR1
## COL2A1 ---> NCOR1
## PRF1 ---> NCOR1
## KRAS ---> NCOR1
## TP53 ---> NCOR1
## BAP1 ---> PIK3CA
##
## Tree score 0.666666666666667
##
## $fit$phylogenies$CRUK0021
## [ ctree - ctree rank 1/1 for CRUK0021 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: EGFR, TP53, CHEK2, CDKN2A
##
## Information transfer
##
## GL ---> CDKN2A
## GL ---> EGFR
## GL ---> CHEK2
## CDKN2A ---> TP53
## EGFR ---> TP53
##
## Tree score 1
##
## $fit$phylogenies$CRUK0022
## [ ctree - ctree rank 1/1 for CRUK0022 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.99 0.99
## 2 2 1 TRUE FALSE 0.85 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R2] :: TP53, EGFR
## \-2 :: CIC
##
## Information transfer
##
## GL ---> EGFR
## EGFR ---> TP53
## TP53 ---> CIC
##
## Tree score 1
##
## $fit$phylogenies$CRUK0023
## [ ctree - ctree rank 1/1 for CRUK0023 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 3 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.99 0.98 0.99 0.95
## 2 4 2 TRUE FALSE 0.01 0.945 0 0
## 3 2 1 TRUE FALSE 0.81 0 0 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R3, R4] :: WRN, KRAS, CDKN2A
## |-2 :: TP53
## \-4 :: PTPRC, KMT2D
##
## Information transfer
##
## GL ---> WRN
## GL ---> KRAS
## GL ---> CDKN2A
## WRN ---> PTPRC
## KRAS ---> PTPRC
## CDKN2A ---> PTPRC
## WRN ---> KMT2D
## KRAS ---> KMT2D
## CDKN2A ---> KMT2D
## WRN ---> TP53
## KRAS ---> TP53
## CDKN2A ---> TP53
##
## Tree score 1
##
## $fit$phylogenies$CRUK0024
## [ ctree - ctree rank 1/1 for CRUK0024 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 3 x 8
## cluster nMuts is.driver is.clonal R1 R3 R4 R6
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1
## 2 3 1 TRUE FALSE 0.88 0.97 0.95 0
## 3 4 1 TRUE FALSE 0.83 0 0 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R6] :: TP53, STK11, POLE, EGFR
## \-3 :: ATM
## \-4 :: NCOR1
##
## Information transfer
##
## GL ---> STK11
## GL ---> POLE
## EGFR ---> TP53
## STK11 ---> EGFR
## TP53 ---> ATM
## POLE ---> ATM
## ATM ---> NCOR1
##
## Tree score 1
##
## $fit$phylogenies$CRUK0025
## [ ctree - ctree rank 1/1 for CRUK0025 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3] :: KRAS, TP53, MGA
##
## Information transfer
##
## GL ---> KRAS
## GL ---> TP53
## KRAS ---> TP53
## KRAS ---> MGA
## TP53 ---> KRAS
##
## Tree score 1
##
## $fit$phylogenies$CRUK0026
## [ ctree - ctree rank 1/1 for CRUK0026 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 0.98 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: TP53, EGFR, RB1, SERPINB13
##
## Information transfer
##
## GL ---> EGFR
## GL ---> SERPINB13
## EGFR ---> TP53
## EGFR ---> RB1
##
## Tree score 1
##
## $fit$phylogenies$CRUK0027
## [ ctree - ctree rank 1/1 for CRUK0027 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.96 1
## 2 2 1 TRUE FALSE 0 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1] :: KRAS, TP53
## \-2 :: PLXNB2
##
## Information transfer
##
## GL ---> KRAS
## GL ---> TP53
## KRAS ---> TP53
## TP53 ---> KRAS
## KRAS ---> PLXNB2
## TP53 ---> PLXNB2
##
## Tree score 1
##
## $fit$phylogenies$CRUK0028
## [ ctree - ctree rank 1/1 for CRUK0028 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.975 0.95
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: APC, EGFR
##
## Information transfer
##
## GL ---> APC
## GL ---> EGFR
##
## Tree score 1
##
## $fit$phylogenies$CRUK0029
## [ ctree - ctree rank 1/1 for CRUK0029 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 10
## cluster nMuts is.driver is.clonal R2 R4 R5 R6 R7 R8
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 0.99 0.98 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R2, R4, R5, R6, R7, R8] :: TP53, NRAS, MGA, CCND1
##
## Information transfer
##
## GL ---> TP53
## GL ---> MGA
## GL ---> CCND1
## TP53 ---> NRAS
##
## Tree score 1
##
## $fit$phylogenies$CRUK0030
## [ ctree - ctree rank 1/1 for CRUK0030 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 1 0.98 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3] :: KRAS, TSC2, U2AF1, TP53, FBXW7, NF1
##
## Information transfer
##
## GL ---> TSC2
## GL ---> U2AF1
## GL ---> FBXW7
## GL ---> KRAS
## GL ---> TP53
## KRAS ---> TP53
## TP53 ---> KRAS
## TP53 ---> NF1
##
## Tree score 1
##
## $fit$phylogenies$CRUK0031
## [ ctree - ctree rank 1/1 for CRUK0031 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1
## 2 6 1 TRUE FALSE 0.88 0.05 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R3] :: KEAP1, CDKN2A, PRF1, FGFR1
## \-6 :: NF1
##
## Information transfer
##
## GL ---> KEAP1
## GL ---> CDKN2A
## GL ---> PRF1
## GL ---> FGFR1
## KEAP1 ---> NF1
## CDKN2A ---> NF1
## PRF1 ---> NF1
## FGFR1 ---> NF1
##
## Tree score 1
##
## $fit$phylogenies$CRUK0032
## [ ctree - ctree rank 1/1 for CRUK0032 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 3 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1
## 2 4 1 TRUE FALSE 0 0.97 0 0.98
## 3 6 1 TRUE FALSE 0 0 0 0.3
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R3] :: ATM, RAD21, U2AF1, RNF43
## \-4 :: CCND1
## \-6 :: ARID1B
##
## Information transfer
##
## GL ---> ATM
## GL ---> RAD21
## GL ---> U2AF1
## GL ---> RNF43
## ATM ---> CCND1
## RAD21 ---> CCND1
## U2AF1 ---> CCND1
## RNF43 ---> CCND1
## CCND1 ---> ARID1B
##
## Tree score 1
##
## $fit$phylogenies$CRUK0033
## [ ctree - ctree rank 1/1 for CRUK0033 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.99 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: KEAP1, CTNNB1
##
## Information transfer
##
## GL ---> KEAP1
## GL ---> CTNNB1
##
## Tree score 1
##
## $fit$phylogenies$CRUK0034
## [ ctree - ctree rank 1/1 for CRUK0034 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 1 1 1
## 2 4 1 TRUE FALSE 0 0.5 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R3] :: ATM, KRAS, PLXNB2
## \-4 :: MGA
##
## Information transfer
##
## GL ---> KRAS
## GL ---> ATM
## KRAS ---> PLXNB2
## ATM ---> MGA
## PLXNB2 ---> MGA
##
## Tree score 1
##
## $fit$phylogenies$CRUK0035
## [ ctree - ctree rank 1/1 for CRUK0035 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal LN1 R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.98 0.98 0.99 0.99
## 2 4 1 TRUE FALSE 0 0.8 0 0.01
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [LN1, R2] :: TP53, FAS
## \-4 :: FLT4
##
## Information transfer
##
## GL ---> TP53
## TP53 ---> FAS
## FAS ---> FLT4
##
## Tree score 1
##
## $fit$phylogenies$CRUK0036
## [ ctree - ctree rank 1/1 for CRUK0036 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 0.99 0.98 0.97 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: KRAS, PIK3CA, KEAP1, ARHGAP35, TERT
##
## Information transfer
##
## GL ---> ARHGAP35
## GL ---> KEAP1
## GL ---> PIK3CA
## ARHGAP35 ---> TERT
## KEAP1 ---> KRAS
## PIK3CA ---> TERT
## TERT ---> KRAS
##
## Tree score 1
##
## $fit$phylogenies$CRUK0037
## [ ctree - ctree rank 1/1 for CRUK0037 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 9
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.99 1 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4, R5] :: NCOA6, CREBBP, KRAS
##
## Information transfer
##
## GL ---> NCOA6
## GL ---> CREBBP
## GL ---> KRAS
##
## Tree score 1
##
## $fit$phylogenies$CRUK0038
## [ ctree - ctree rank 1/1 for CRUK0038 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.99
## 2 3 1 TRUE FALSE 0 0.38
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1] :: KRAS
## \-3 :: KMT2D
##
## Information transfer
##
## GL ---> KRAS
## KRAS ---> KMT2D
##
## Tree score 1
##
## $fit$phylogenies$CRUK0039
## [ ctree - ctree rank 1/1 for CRUK0039 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3] :: KRAS, CMTR2, NF1, PHOX2B
##
## Information transfer
##
## GL ---> KRAS
## GL ---> CMTR2
## GL ---> NF1
## GL ---> PHOX2B
##
## Tree score 1
##
## $fit$phylogenies$CRUK0040
## [ ctree - ctree rank 1/1 for CRUK0040 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 0.99 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: NCOR1, RAD21, KRAS, GATA3
##
## Information transfer
##
## GL ---> KRAS
## GL ---> RAD21
## GL ---> GATA3
## KRAS ---> NCOR1
##
## Tree score 1
##
## $fit$phylogenies$CRUK0041
## [ ctree - ctree rank 1/1 for CRUK0041 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.98 0.99 0.99 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: BRAF, TERT, EGFR
##
## Information transfer
##
## GL ---> BRAF
## GL ---> EGFR
## BRAF ---> TERT
##
## Tree score 1
##
## $fit$phylogenies$CRUK0042
## [ ctree - ctree rank 1/1 for CRUK0042 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 5
## cluster nMuts is.driver is.clonal R1
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 1 TRUE TRUE 0.91
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1] :: KRAS
##
## Information transfer
##
## GL ---> KRAS
##
## Tree score 1
##
## $fit$phylogenies$CRUK0043
## [ ctree - ctree rank 1/1 for CRUK0043 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: MET
##
## Information transfer
##
## GL ---> MET
##
## Tree score 1
##
## $fit$phylogenies$CRUK0044
## [ ctree - ctree rank 1/1 for CRUK0044 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: KRAS
##
## Information transfer
##
## GL ---> KRAS
##
## Tree score 1
##
## $fit$phylogenies$CRUK0045
## [ ctree - ctree rank 1/1 for CRUK0045 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.98 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R3] :: BAP1
##
## Information transfer
##
## GL ---> BAP1
##
## Tree score 1
##
## $fit$phylogenies$CRUK0046
## [ ctree - ctree rank 1/1 for CRUK0046 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 1 0.98 0.995 0.96
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: KEAP1, APC
##
## Information transfer
##
## GL ---> KEAP1
## GL ---> APC
##
## Tree score 1
##
## $fit$phylogenies$CRUK0047
## [ ctree - ctree rank 1/1 for CRUK0047 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 0.99 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: STK11, APC, KRAS, MYC
##
## Information transfer
##
## GL ---> MYC
## GL ---> STK11
## GL ---> APC
## MYC ---> KRAS
## STK11 ---> KRAS
##
## Tree score 1
##
## $fit$phylogenies$CRUK0048
## [ ctree - ctree rank 1/1 for CRUK0048 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 7 TRUE TRUE 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3] :: APC, PRDM1, ARHGAP35, TP53, BRAF, EGFR, MYC
##
## Information transfer
##
## GL ---> EGFR
## GL ---> APC
## GL ---> PRDM1
## GL ---> BRAF
## GL ---> MYC
## EGFR ---> TP53
## EGFR ---> ARHGAP35
## TP53 ---> ARHGAP35
##
## Tree score 1
##
## $fit$phylogenies$CRUK0049
## [ ctree - ctree rank 1/1 for CRUK0049 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: RB1, TP53, COL2A1, EGFR, KRAS
##
## Information transfer
##
## GL ---> EGFR
## GL ---> COL2A1
## GL ---> KRAS
## GL ---> TP53
## EGFR ---> TP53
## EGFR ---> RB1
## KRAS ---> TP53
## TP53 ---> KRAS
##
## Tree score 1
##
## $fit$phylogenies$CRUK0050
## [ ctree - ctree rank 1/1 for CRUK0050 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 9
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.99 0.99 0.99 1 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4, R5] :: KRAS, STK11, MYC
##
## Information transfer
##
## GL ---> MYC
## GL ---> STK11
## MYC ---> KRAS
## STK11 ---> KRAS
##
## Tree score 1
##
## $fit$phylogenies$CRUK0051
## [ ctree - ctree rank 1/1 for CRUK0051 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1
## 2 3 1 TRUE FALSE 0.97 0 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R3, R4] :: KRAS, FBXW7, TP53, EGFR
## \-3 :: EP300
##
## Information transfer
##
## GL ---> EGFR
## GL ---> FBXW7
## GL ---> KRAS
## GL ---> TP53
## EGFR ---> TP53
## KRAS ---> TP53
## TP53 ---> KRAS
## FBXW7 ---> EP300
## KRAS ---> EP300
## TP53 ---> EP300
##
## Tree score 1
##
## $fit$phylogenies$CRUK0052
## [ ctree - ctree rank 1/1 for CRUK0052 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R1 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 8 TRUE TRUE 1 1 1
## 2 2 1 TRUE FALSE 0 0 0.86
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R3] :: KMT2D, KRAS, NOTCH2, MGA, KEAP1, TP53, NF1, SGK223
## \-2 :: UBR5
##
## Information transfer
##
## GL ---> KEAP1
## GL ---> NOTCH2
## GL ---> SGK223
## GL ---> KRAS
## GL ---> TP53
## KEAP1 ---> KRAS
## KEAP1 ---> NF1
## KRAS ---> MGA
## KRAS ---> TP53
## KRAS ---> KMT2D
## MGA ---> NF1
## TP53 ---> KRAS
## TP53 ---> NF1
## KMT2D ---> UBR5
## NOTCH2 ---> UBR5
## NF1 ---> UBR5
## SGK223 ---> UBR5
## KRAS ---> UBR5
## TP53 ---> UBR5
##
## Tree score 1
##
## $fit$phylogenies$CRUK0054
## [ ctree - ctree rank 1/1 for CRUK0054 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: EGFR
##
## Information transfer
##
## GL ---> EGFR
##
## Tree score 1
##
## $fit$phylogenies$CRUK0055
## [ ctree - ctree rank 1/1 for CRUK0055 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 5
## cluster nMuts is.driver is.clonal R2
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 2 TRUE TRUE 1
## 2 2 1 TRUE FALSE 0.32
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: FANCM, UBR5
## \-2 :: FAT1
##
## Information transfer
##
## GL ---> FANCM
## GL ---> UBR5
## FANCM ---> FAT1
## UBR5 ---> FAT1
##
## Tree score 1
##
## $fit$phylogenies$CRUK0056
## [ ctree - ctree rank 1/1 for CRUK0056 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 1 1 1
## 2 3 1 TRUE FALSE 0 0.12 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1] :: RASA1, CREBBP
## \-3 :: TP53
##
## Information transfer
##
## GL ---> RASA1
## GL ---> CREBBP
## RASA1 ---> TP53
## CREBBP ---> TP53
##
## Tree score 1
##
## $fit$phylogenies$CRUK0057
## [ ctree - ctree rank 1/1 for CRUK0057 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: KRAS, SMARCA4, TSC2, DNM2, TERT
##
## Information transfer
##
## GL ---> TERT
## GL ---> SMARCA4
## GL ---> TSC2
## TERT ---> KRAS
## TERT ---> DNM2
##
## Tree score 1
##
## $fit$phylogenies$CRUK0058
## [ ctree - ctree rank 1/1 for CRUK0058 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.98 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: TP53, EGFR
##
## Information transfer
##
## GL ---> EGFR
## EGFR ---> TP53
##
## Tree score 1
##
## $fit$phylogenies$CRUK0059
## [ ctree - ctree rank 1/1 for CRUK0059 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: KRAS
##
## Information transfer
##
## GL ---> KRAS
##
## Tree score 1
##
## $fit$phylogenies$CRUK0060
## [ ctree - ctree rank 1/1 for CRUK0060 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 5
## cluster nMuts is.driver is.clonal R1
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 11 TRUE TRUE 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1] :: SERPINB13, ARID2, COL5A2, FANCM, PHOX2B, COL2A1, RASA1, NF1, NCOA6, NOTCH2, KMT2C
##
## Information transfer
##
## GL ---> NCOA6
## GL ---> NF1
## GL ---> SERPINB13
## GL ---> ARID2
## GL ---> PHOX2B
## GL ---> COL2A1
## GL ---> RASA1
## GL ---> NOTCH2
## GL ---> KMT2C
## NCOA6 ---> COL5A2
## NF1 ---> FANCM
## SERPINB13 ---> COL5A2
##
## Tree score 1
##
## $fit$phylogenies$CRUK0061
## [ ctree - ctree rank 1/1 for CRUK0061 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 0.99 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: STK11
##
## Information transfer
##
## GL ---> STK11
##
## Tree score 1
##
## $fit$phylogenies$CRUK0062
## [ ctree - ctree rank 1/2 for CRUK0062 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 4 x 11
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5 R6
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 4 4 TRUE TRUE 0.99 0.99 0.98 0.97 0.99 0.99
## 2 1 1 TRUE FALSE 0 0.01 0 0 0 0.94
## 3 16 1 TRUE FALSE 0.93 0.86 0.08 0.02 0.12 0
## 4 2 1 TRUE FALSE 0.84 0.83 0.02 0 0 0
## # … with 1 more variable: R7 <dbl>
##
## Tree shape (drivers annotated)
##
## \-GL
## \-4 :: TP53, PIK3CA, SOX2, CCND1
## |-16 :: UBR5
## | \-2 :: PLXNB2
## \-1 :: FAS
##
## Information transfer
##
## GL ---> TP53
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> CCND1
## TP53 ---> UBR5
## PIK3CA ---> UBR5
## SOX2 ---> UBR5
## CCND1 ---> UBR5
## TP53 ---> FAS
## PIK3CA ---> FAS
## SOX2 ---> FAS
## CCND1 ---> FAS
## UBR5 ---> PLXNB2
##
## Tree score 0.75
##
## $fit$phylogenies$CRUK0063
## [ ctree - ctree rank 1/6 for CRUK0063 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 4 x 9
## cluster nMuts is.driver is.clonal R3 R4 R5 R6 R7
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 2 7 TRUE TRUE 0.93 0.99 0.99 0.99 1
## 2 1 2 TRUE FALSE 0 0.99 0.99 0.98 1
## 3 10 1 TRUE FALSE 0 0.99 0.99 0.98 1
## 4 6 1 TRUE FALSE 0 0.02 0.7 0.36 0.55
##
## Tree shape (drivers annotated)
##
## \-GL
## \-2 [R3] :: PIK3CA, TP53, FBXW7, CDKN2A, SOX2, TERT, PRF1
## \-10 :: EP300
## \-1 :: NF1, CYLD
## \-6 :: FANCM
##
## Information transfer
##
## GL ---> CDKN2A
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> FBXW7
## GL ---> PRF1
## CDKN2A ---> TP53
## PIK3CA ---> TERT
## SOX2 ---> TERT
## TP53 ---> TERT
## FBXW7 ---> EP300
## TERT ---> EP300
## PRF1 ---> EP300
## EP300 ---> NF1
## EP300 ---> CYLD
## NF1 ---> FANCM
## CYLD ---> FANCM
##
## Tree score 0.125
##
## $fit$phylogenies$CRUK0064
## [ ctree - ctree rank 1/1 for CRUK0064 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 2 2 TRUE FALSE 0.64 0.11
## 2 1 1 TRUE TRUE 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53
## \-2 :: MLH1, FAT1
##
## Information transfer
##
## GL ---> TP53
## TP53 ---> MLH1
## TP53 ---> FAT1
##
## Tree score 1
##
## $fit$phylogenies$CRUK0065
## [ ctree - ctree rank 1/1 for CRUK0065 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 3 x 10
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5 R6
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 0.99 0.99 1 1 1
## 2 2 3 TRUE FALSE 0 0 0 0 0.48 0
## 3 6 2 TRUE FALSE 0 0 0 0 0.01 0.83
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: TP53, NFE2L2, PIK3CA, SOX2
## |-2 :: MLH1, PTPRC, UBR5
## \-6 :: NOTCH1, NCOA6
##
## Information transfer
##
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> TP53
## PIK3CA ---> NFE2L2
## SOX2 ---> NFE2L2
## TP53 ---> NFE2L2
## NFE2L2 ---> MLH1
## NFE2L2 ---> PTPRC
## NFE2L2 ---> UBR5
## NFE2L2 ---> NOTCH1
## NFE2L2 ---> NCOA6
##
## Tree score 1
##
## $fit$phylogenies$CRUK0066
## [ ctree - ctree rank 1/1 for CRUK0066 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 7 TRUE TRUE 0.99 1 1 0.99
## 2 9 1 TRUE FALSE 0 0.91 0.01 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R4] :: TP53, NOTCH1, CDKN2A, WRN, PDGFRA, TERT, NCOA6
## \-9 :: COL5A2
##
## Information transfer
##
## GL ---> CDKN2A
## GL ---> WRN
## GL ---> PDGFRA
## CDKN2A ---> TP53
## TP53 ---> NOTCH1
## TP53 ---> TERT
## TP53 ---> NCOA6
## WRN ---> TP53
## NOTCH1 ---> COL5A2
## PDGFRA ---> COL5A2
## TERT ---> COL5A2
## NCOA6 ---> COL5A2
##
## Tree score 1
##
## $fit$phylogenies$CRUK0067
## [ ctree - ctree rank 1/1 for CRUK0067 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 0.99 1
## 2 2 1 TRUE FALSE 0.61 0.83
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: NOTCH1, TP53, PIK3CA, SOX2, CDKN2A
## \-2 :: NFE2L2
##
## Information transfer
##
## GL ---> CDKN2A
## GL ---> PIK3CA
## GL ---> SOX2
## CDKN2A ---> TP53
## PIK3CA ---> NOTCH1
## SOX2 ---> NOTCH1
## TP53 ---> NOTCH1
## NOTCH1 ---> NFE2L2
##
## Tree score 1
##
## $fit$phylogenies$CRUK0068
## [ ctree - ctree rank 1/1 for CRUK0068 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 4 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 0.99 1 1 1
## 2 3 1 TRUE FALSE 0.5 0 0 0
## 3 4 1 TRUE FALSE 0.98 0.37 0.99 0.01
## 4 9 1 TRUE FALSE 0 0 0 0.69
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53, PTEN, KMT2D, PIK3CA, SOX2
## |-4 :: SETD2
## | \-3 :: MGA
## \-9 :: TERT
##
## Information transfer
##
## GL ---> TP53
## GL ---> PTEN
## GL ---> KMT2D
## GL ---> PIK3CA
## GL ---> SOX2
## TP53 ---> SETD2
## PTEN ---> SETD2
## KMT2D ---> SETD2
## PIK3CA ---> SETD2
## SOX2 ---> SETD2
## TP53 ---> TERT
## PTEN ---> TERT
## KMT2D ---> TERT
## PIK3CA ---> TERT
## SOX2 ---> TERT
## SETD2 ---> MGA
##
## Tree score 1
##
## $fit$phylogenies$CRUK0069
## [ ctree - ctree rank 1/1 for CRUK0069 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 9
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1 1
## 2 13 1 TRUE FALSE 0.93 0.42 0.32 0.94 0.96
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: TP53, FAT1, PDGFRA, FGFR1
## \-13 :: KRAS
##
## Information transfer
##
## GL ---> TP53
## GL ---> PDGFRA
## GL ---> FGFR1
## TP53 ---> FAT1
## FAT1 ---> KRAS
## PDGFRA ---> KRAS
## FGFR1 ---> KRAS
##
## Tree score 1
##
## $fit$phylogenies$CRUK0070
## [ ctree - ctree rank 1/1 for CRUK0070 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 3 x 9
## cluster nMuts is.driver is.clonal R1 R2 R4 R6 R7
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1 1
## 2 2 1 TRUE FALSE 0 0 0 0.95 0.98
## 3 3 1 TRUE FALSE 0.95 0.96 0.98 0 0.01
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: DNM2, TP53, COL5A2, SOX2
## |-3 :: NFE2L2
## \-2 :: CBLB
##
## Information transfer
##
## GL ---> SOX2
## GL ---> TP53
## SOX2 ---> COL5A2
## TP53 ---> DNM2
## TP53 ---> COL5A2
## DNM2 ---> CBLB
## COL5A2 ---> CBLB
## DNM2 ---> NFE2L2
## COL5A2 ---> NFE2L2
##
## Tree score 1
##
## $fit$phylogenies$CRUK0071
## [ ctree - ctree rank 1/1 for CRUK0071 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 10
## cluster nMuts is.driver is.clonal R1 R2 R3 R5 R6 R7
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 1 0.99 1 1 1 1
## 2 4 1 TRUE FALSE 0 0.570 0 0 0 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R3, R5, R6, R7] :: CMTR2, PIK3CA, SOX2
## \-4 :: UBR5
##
## Information transfer
##
## GL ---> CMTR2
## GL ---> PIK3CA
## GL ---> SOX2
## CMTR2 ---> UBR5
## PIK3CA ---> UBR5
## SOX2 ---> UBR5
##
## Tree score 1
##
## $fit$phylogenies$CRUK0072
## [ ctree - ctree rank 1/1 for CRUK0072 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 1 0.99 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R4] :: TP53, NFE2L2, PIK3CA, SOX2, EGFR, MYC
##
## Information transfer
##
## GL ---> EGFR
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> MYC
## EGFR ---> TP53
## PIK3CA ---> NFE2L2
## SOX2 ---> NFE2L2
## TP53 ---> NFE2L2
##
## Tree score 1
##
## $fit$phylogenies$CRUK0073
## [ ctree - ctree rank 1/1 for CRUK0073 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 8 TRUE TRUE 1 1
## 2 2 1 TRUE FALSE 0 0.93
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1] :: CDKN2A, DICER1, NFE2L2, FAT1, KMT2D, NOTCH2, FGFR1, MYC
## \-2 :: PLXNB2
##
## Information transfer
##
## GL ---> CDKN2A
## GL ---> FAT1
## GL ---> FGFR1
## GL ---> DICER1
## GL ---> NOTCH2
## GL ---> MYC
## CDKN2A ---> NFE2L2
## CDKN2A ---> KMT2D
## FAT1 ---> NFE2L2
## FGFR1 ---> NFE2L2
## DICER1 ---> PLXNB2
## NFE2L2 ---> PLXNB2
## KMT2D ---> PLXNB2
## NOTCH2 ---> PLXNB2
## MYC ---> PLXNB2
##
## Tree score 1
##
## $fit$phylogenies$CRUK0074
## [ ctree - ctree rank 1/1 for CRUK0074 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 0.99 1
## 2 3 1 TRUE FALSE 0 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1] :: TP53, NFE2L2, PIK3CA, SOX2, CCND1
## \-3 :: UBR5
##
## Information transfer
##
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> TP53
## GL ---> CCND1
## PIK3CA ---> NFE2L2
## SOX2 ---> NFE2L2
## TP53 ---> NFE2L2
## NFE2L2 ---> UBR5
## CCND1 ---> UBR5
##
## Tree score 1
##
## $fit$phylogenies$CRUK0075
## [ ctree - ctree rank 1/1 for CRUK0075 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 7 TRUE TRUE 1 0.99
## 2 2 1 TRUE FALSE 0.15 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: NOTCH1, RASA1, TP53, FAT1, MGA, PIK3CA, FGFR1
## \-2 :: NFE2L2
##
## Information transfer
##
## GL ---> PIK3CA
## GL ---> RASA1
## GL ---> MGA
## GL ---> FGFR1
## PIK3CA ---> NOTCH1
## RASA1 ---> TP53
## TP53 ---> NOTCH1
## TP53 ---> FAT1
## NOTCH1 ---> NFE2L2
## FAT1 ---> NFE2L2
## MGA ---> NFE2L2
## FGFR1 ---> NFE2L2
##
## Tree score 1
##
## $fit$phylogenies$CRUK0076
## [ ctree - ctree rank 1/3 for CRUK0076 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 3 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 1 1 1 1
## 2 2 1 TRUE FALSE 0.93 0 0.28 0
## 3 3 1 TRUE FALSE 0.93 0 0.81 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R2, R4] :: SERPINB13, TP53, ARID1B, PIK3CA, SOX2, FGFR1
## \-3 :: COL5A2
## \-2 :: NCOR1
##
## Information transfer
##
## GL ---> TP53
## GL ---> SERPINB13
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> FGFR1
## TP53 ---> ARID1B
## SERPINB13 ---> COL5A2
## ARID1B ---> COL5A2
## PIK3CA ---> COL5A2
## SOX2 ---> COL5A2
## FGFR1 ---> COL5A2
## COL5A2 ---> NCOR1
##
## Tree score 0.444444444444444
##
## $fit$phylogenies$CRUK0077
## [ ctree - ctree rank 1/1 for CRUK0077 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 1 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: TP53, LATS1, KEAP1
##
## Information transfer
##
## GL ---> TP53
## GL ---> KEAP1
## TP53 ---> LATS1
##
## Tree score 1
##
## $fit$phylogenies$CRUK0078
## [ ctree - ctree rank 1/1 for CRUK0078 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R2, R3, R4] :: PLXNB2, PTEN, PIK3CA, SOX2, FGFR1
##
## Information transfer
##
## GL ---> FGFR1
## GL ---> PTEN
## GL ---> PIK3CA
## GL ---> SOX2
## FGFR1 ---> PLXNB2
##
## Tree score 1
##
## $fit$phylogenies$CRUK0079
## [ ctree - ctree rank 1/1 for CRUK0079 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 1 0.99 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: FAT1, TP53, POLE, PIK3CA, SOX2, FGFR1
##
## Information transfer
##
## GL ---> TP53
## GL ---> POLE
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> FGFR1
## TP53 ---> FAT1
##
## Tree score 1
##
## $fit$phylogenies$CRUK0080
## [ ctree - ctree rank 1/1 for CRUK0080 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 8
## cluster nMuts is.driver is.clonal R3 R4 R5 R6
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1
## 2 3 1 TRUE FALSE 0 0 0.97 0.83
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R3, R4] :: TP53, WT1, EGFR, CCND1
## \-3 :: IKZF1
##
## Information transfer
##
## GL ---> EGFR
## GL ---> WT1
## GL ---> CCND1
## EGFR ---> TP53
## TP53 ---> IKZF1
## WT1 ---> IKZF1
## CCND1 ---> IKZF1
##
## Tree score 1
##
## $fit$phylogenies$CRUK0081
## [ ctree - ctree rank 1/1 for CRUK0081 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 6
## cluster nMuts is.driver is.clonal R1 R5
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 1 0.99
## 2 3 1 TRUE FALSE 0.93 0.01
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 :: NOTCH1, TP53, CDKN2A, FAT1, FANCC
## \-3 :: CYLD
##
## Information transfer
##
## GL ---> CDKN2A
## CDKN2A ---> TP53
## TP53 ---> NOTCH1
## TP53 ---> FAT1
## TP53 ---> FANCC
## NOTCH1 ---> CYLD
## FAT1 ---> CYLD
## FANCC ---> CYLD
##
## Tree score 1
##
## $fit$phylogenies$CRUK0082
## [ ctree - ctree rank 1/1 for CRUK0082 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 9
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 8 TRUE TRUE 1 1 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4, R5] :: TP53, WT1, PTEN, COL5A2, KMT2D, PIK3CA, SOX2, FGFR1
##
## Information transfer
##
## GL ---> FGFR1
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> TP53
## GL ---> WT1
## GL ---> PTEN
## GL ---> KMT2D
## FGFR1 ---> COL5A2
## PIK3CA ---> COL5A2
## SOX2 ---> COL5A2
## TP53 ---> COL5A2
##
## Tree score 1
##
## $fit$phylogenies$CRUK0083
## [ ctree - ctree rank 1/1 for CRUK0083 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 7 TRUE TRUE 1 1 1 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: TP53, FBXW7, RASA1, PIK3CA, SOX2, FGFR1, MYC
##
## Information transfer
##
## GL ---> RASA1
## GL ---> FBXW7
## GL ---> PIK3CA
## GL ---> SOX2
## GL ---> FGFR1
## GL ---> MYC
## RASA1 ---> TP53
##
## Tree score 1
##
## $fit$phylogenies$CRUK0084
## [ ctree - ctree rank 1/1 for CRUK0084 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 1 TRUE TRUE 1 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: CREBBP
##
## Information transfer
##
## GL ---> CREBBP
##
## Tree score 1
##
## $fit$phylogenies$CRUK0085
## [ ctree - ctree rank 1/1 for CRUK0085 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: CHEK2, CREBBP, LATS1, FANCM
##
## Information transfer
##
## GL ---> CHEK2
## GL ---> CREBBP
## GL ---> LATS1
## GL ---> FANCM
##
## Tree score 1
##
## $fit$phylogenies$CRUK0086
## [ ctree - ctree rank 1/1 for CRUK0086 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R4] :: TP53, ARID2, FAT1
##
## Information transfer
##
## GL ---> TP53
## GL ---> ARID2
## TP53 ---> FAT1
##
## Tree score 1
##
## $fit$phylogenies$CRUK0087
## [ ctree - ctree rank 1/1 for CRUK0087 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 4 TRUE TRUE 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3] :: NFE2L2, TP53, ASXL1, PIK3CA
##
## Information transfer
##
## GL ---> PIK3CA
## GL ---> TP53
## GL ---> ASXL1
## PIK3CA ---> NFE2L2
## TP53 ---> NFE2L2
##
## Tree score 1
##
## $fit$phylogenies$CRUK0088
## [ ctree - ctree rank 1/1 for CRUK0088 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: CUX1, TP53
##
## Information transfer
##
## GL ---> CUX1
## GL ---> TP53
##
## Tree score 1
##
## $fit$phylogenies$CRUK0089
## [ ctree - ctree rank 1/1 for CRUK0089 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 5
## cluster nMuts is.driver is.clonal R2
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 3 TRUE TRUE 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R2] :: PIK3CA, SMAD4, KEAP1
##
## Information transfer
##
## GL ---> PIK3CA
## GL ---> SMAD4
## GL ---> KEAP1
##
## Tree score 1
##
## $fit$phylogenies$CRUK0090
## [ ctree - ctree rank 1/1 for CRUK0090 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 5 TRUE TRUE 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: CDKN2A, NCOA6, CUX1, COL2A1, NRAS
##
## Information transfer
##
## GL ---> CDKN2A
## GL ---> NCOA6
## GL ---> CUX1
## GL ---> COL2A1
## GL ---> NRAS
##
## Tree score 1
##
## $fit$phylogenies$CRUK0091
## [ ctree - ctree rank 1/1 for CRUK0091 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 5
## cluster nMuts is.driver is.clonal R2
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 3 TRUE TRUE 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R2] :: TP53, SMARCA4, CDKN2A
##
## Information transfer
##
## GL ---> CDKN2A
## GL ---> SMARCA4
## CDKN2A ---> TP53
##
## Tree score 1
##
## $fit$phylogenies$CRUK0092
## [ ctree - ctree rank 1/1 for CRUK0092 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 5
## cluster nMuts is.driver is.clonal R1
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 5 TRUE TRUE 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1] :: TP53, SMAD4, RASA1, CBLB, PIK3CA
##
## Information transfer
##
## GL ---> RASA1
## GL ---> PIK3CA
## RASA1 ---> TP53
## TP53 ---> SMAD4
## TP53 ---> CBLB
##
## Tree score 1
##
## $fit$phylogenies$CRUK0093
## [ ctree - ctree rank 1/1 for CRUK0093 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 5
## cluster nMuts is.driver is.clonal R1
## <chr> <int> <lgl> <lgl> <dbl>
## 1 1 7 TRUE TRUE 0.96
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1] :: DICER1, CDKN2A, COL2A1, GATA3, CIC, COL5A2, TP53
##
## Information transfer
##
## GL ---> CDKN2A
## GL ---> DICER1
## GL ---> COL2A1
## GL ---> GATA3
## CDKN2A ---> TP53
## CDKN2A ---> COL5A2
## TP53 ---> CIC
## TP53 ---> COL5A2
##
## Tree score 1
##
## $fit$phylogenies$CRUK0094
## [ ctree - ctree rank 1/1 for CRUK0094 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R2 R3 R4
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.98 0.98 0.97 0.99
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4] :: SMARCA4, TERT
##
## Information transfer
##
## GL ---> SMARCA4
## GL ---> TERT
##
## Tree score 1
##
## $fit$phylogenies$CRUK0095
## [ ctree - ctree rank 1/1 for CRUK0095 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.99 0.99 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3] :: TP53, NF1, RASA1
##
## Information transfer
##
## GL ---> RASA1
## RASA1 ---> TP53
## TP53 ---> NF1
##
## Tree score 1
##
## $fit$phylogenies$CRUK0096
## [ ctree - ctree rank 1/1 for CRUK0096 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 11
## cluster nMuts is.driver is.clonal R1 R2 R3 R4 R5 R6
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 1 1 1 1 1 1
## # … with 1 more variable: R7 <dbl>
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3, R4, R5, R6, R7] :: KRAS, SGK223, MAP3K1
##
## Information transfer
##
## GL ---> KRAS
## GL ---> SGK223
## GL ---> MAP3K1
##
## Tree score 1
##
## $fit$phylogenies$CRUK0097
## [ ctree - ctree rank 1/1 for CRUK0097 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 6
## cluster nMuts is.driver is.clonal R1 R2
## <chr> <int> <lgl> <lgl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 0.995 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2] :: TP53, PTEN
##
## Information transfer
##
## GL ---> TP53
## GL ---> PTEN
##
## Tree score 1
##
## $fit$phylogenies$CRUK0098
## [ ctree - ctree rank 1/1 for CRUK0098 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 2 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 2 TRUE TRUE 1 1 1
## 2 3 1 TRUE FALSE 0.96 0.91 0
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R3] :: TP53, PTEN
## \-3 :: UBR5
##
## Information transfer
##
## GL ---> TP53
## GL ---> PTEN
## TP53 ---> UBR5
## PTEN ---> UBR5
##
## Tree score 1
##
## $fit$phylogenies$CRUK0099
## [ ctree - ctree rank 1/1 for CRUK0099 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 8
## cluster nMuts is.driver is.clonal R1 R3 R6 R7
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE TRUE 0.95 0.97 0.91 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R3, R6, R7] :: STK11, KEAP1, TP53
##
## Information transfer
##
## GL ---> STK11
## GL ---> KEAP1
## GL ---> TP53
##
## Tree score 1
##
## $fit$phylogenies$CRUK0100
## [ ctree - ctree rank 1/1 for CRUK0100 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 1 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 6 TRUE TRUE 1 1 1
##
## Tree shape (drivers annotated)
##
## \-GL
## \-1 [R1, R2, R3] :: TP53, PHOX2B, COL5A2, STK11, SPEN, CDKN2A
##
## Information transfer
##
## GL ---> CDKN2A
## GL ---> PHOX2B
## GL ---> STK11
## GL ---> SPEN
## CDKN2A ---> TP53
## CDKN2A ---> COL5A2
## TP53 ---> COL5A2
##
## Tree score 1
##
##
## $fit$clones_to_expand
## $fit$clones_to_expand$CRUK0001
## $fit$clones_to_expand$CRUK0001$`1`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 NF1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0001$`2`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 ARHGAP35
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0001$`3`
## # A tbl_graph: 4 nodes and 2 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 4 x 1 (active)
## cluster
## <chr>
## 1 EGFR
## 2 WRN
## 3 TP53
## 4 MGA
## #
## # Edge Data: 2 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 3 1 0.5
## 2 2 3 1 0.5
##
## $fit$clones_to_expand$CRUK0001$`5`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 PASK
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0002
## $fit$clones_to_expand$CRUK0002$`1`
## # A tbl_graph: 3 nodes and 0 edges
## #
## # A rooted forest with 3 trees
## #
## # Node Data: 3 x 1 (active)
## cluster
## <chr>
## 1 RB1
## 2 IKZF1
## 3 KRAS
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0002$`2`
## # A tbl_graph: 2 nodes and 1 edges
## #
## # A rooted tree
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 MET
## 2 TERT
## #
## # Edge Data: 1 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
##
## $fit$clones_to_expand$CRUK0002$`5`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 NF1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0002$`6`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 EP300
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0003
## $fit$clones_to_expand$CRUK0003$`1`
## # A tbl_graph: 3 nodes and 0 edges
## #
## # A rooted forest with 3 trees
## #
## # Node Data: 3 x 1 (active)
## cluster
## <chr>
## 1 PIK3CA
## 2 EGFR
## 3 CDKN2A
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0003$`4`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 CTNNB1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0004
## $fit$clones_to_expand$CRUK0004$`1`
## # A tbl_graph: 2 nodes and 0 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 SMAD4
## 2 NOTCH1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0004$`2`
## # A tbl_graph: 2 nodes and 1 edges
## #
## # A rooted tree
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 EGFR
## 2 TP53
## #
## # Edge Data: 1 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
##
##
## $fit$clones_to_expand$CRUK0005
## $fit$clones_to_expand$CRUK0005$`1`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 NRAS
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0005$`2`
## # A tbl_graph: 5 nodes and 2 edges
## #
## # A rooted forest with 3 trees
## #
## # Node Data: 5 x 1 (active)
## cluster
## <chr>
## 1 BRAF
## 2 TP53
## 3 CMTR2
## 4 PASK
## 5 TERT
## #
## # Edge Data: 2 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 5 1 0.333
## 2 2 5 2 0.667
##
##
## $fit$clones_to_expand$CRUK0006
## $fit$clones_to_expand$CRUK0006$`1`
## # A tbl_graph: 4 nodes and 2 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 4 x 1 (active)
## cluster
## <chr>
## 1 TP53
## 2 PLXNB2
## 3 KEAP1
## 4 TERT
## #
## # Edge Data: 2 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
## 2 1 4 2 1
##
## $fit$clones_to_expand$CRUK0006$`2`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 MAP3K1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0006$`7`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 FANCC
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0007
## $fit$clones_to_expand$CRUK0007$`1`
## # A tbl_graph: 3 nodes and 0 edges
## #
## # A rooted forest with 3 trees
## #
## # Node Data: 3 x 1 (active)
## cluster
## <chr>
## 1 PIK3CA
## 2 EGFR
## 3 SGK223
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0008
## $fit$clones_to_expand$CRUK0008$`2`
## # A tbl_graph: 5 nodes and 0 edges
## #
## # A rooted forest with 5 trees
## #
## # Node Data: 5 x 1 (active)
## cluster
## <chr>
## 1 KEAP1
## 2 STK11
## 3 PRDM1
## 4 U2AF1
## 5 MYC
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0008$`3`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 ARID2
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0009
## $fit$clones_to_expand$CRUK0009$`1`
## # A tbl_graph: 6 nodes and 2 edges
## #
## # A rooted forest with 4 trees
## #
## # Node Data: 6 x 1 (active)
## cluster
## <chr>
## 1 TP53
## 2 BRAF
## 3 ARHGAP35
## 4 KMT2C
## 5 NFE2L2
## 6 MET
## #
## # Edge Data: 2 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 3 1 1
## 2 1 5 3 1
##
## $fit$clones_to_expand$CRUK0009$`2`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 TERT
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0010
## $fit$clones_to_expand$CRUK0010$`1`
## # A tbl_graph: 3 nodes and 0 edges
## #
## # A rooted forest with 3 trees
## #
## # Node Data: 3 x 1 (active)
## cluster
## <chr>
## 1 SETD2
## 2 EGFR
## 3 TERT
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0011
## $fit$clones_to_expand$CRUK0011$`1`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 KRAS
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0011$`3`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 FLT4
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0012
## $fit$clones_to_expand$CRUK0012$`1`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 EGFR
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0013
## $fit$clones_to_expand$CRUK0013$`1`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 STK11
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0013$`2`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 NOTCH1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0013$`3`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 KRAS
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0013$`4`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 EGFR
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0014
## $fit$clones_to_expand$CRUK0014$`1`
## # A tbl_graph: 2 nodes and 2 edges
## #
## # A directed simple graph with 1 component
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 KRAS
## 2 TP53
## #
## # Edge Data: 2 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
## 2 2 1 2 1
##
## $fit$clones_to_expand$CRUK0014$`2`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 RNF43
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0015
## $fit$clones_to_expand$CRUK0015$`1`
## # A tbl_graph: 2 nodes and 0 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 BAP1
## 2 EGFR
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0015$`2`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 TP53
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0015$`3`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 RB1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0016
## $fit$clones_to_expand$CRUK0016$`1`
## # A tbl_graph: 6 nodes and 4 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 6 x 1 (active)
## cluster
## <chr>
## 1 CDKN2A
## 2 TP53
## 3 FAT1
## 4 SPEN
## 5 CBLB
## 6 TERT
## #
## # Edge Data: 4 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
## 2 2 5 1 1
## 3 2 3 1 1
## # … with 1 more row
##
## $fit$clones_to_expand$CRUK0016$`2`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 ASXL1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0016$`6`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 PTPRC
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0016$`10`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 DNM2
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0016$`16`
## # A tbl_graph: 2 nodes and 0 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 LATS1
## 2 ARID1B
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0017
## $fit$clones_to_expand$CRUK0017$`1`
## # A tbl_graph: 5 nodes and 3 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 5 x 1 (active)
## cluster
## <chr>
## 1 KEAP1
## 2 MYC
## 3 TP53
## 4 ARID1B
## 5 ARID2
## #
## # Edge Data: 3 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 5 1 0.5
## 2 2 5 1 0.5
## 3 3 4 1 1
##
## $fit$clones_to_expand$CRUK0017$`3`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 KRAS
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0018
## $fit$clones_to_expand$CRUK0018$`1`
## # A tbl_graph: 4 nodes and 1 edges
## #
## # A rooted forest with 3 trees
## #
## # Node Data: 4 x 1 (active)
## cluster
## <chr>
## 1 KRAS
## 2 CMTR2
## 3 MGA
## 4 COL5A2
## #
## # Edge Data: 1 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 3 1 1
##
##
## $fit$clones_to_expand$CRUK0019
## $fit$clones_to_expand$CRUK0019$`1`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 EGFR
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0020
## $fit$clones_to_expand$CRUK0020$`1`
## # A tbl_graph: 7 nodes and 6 edges
## #
## # A directed simple graph with 3 components
## #
## # Node Data: 7 x 1 (active)
## cluster
## <chr>
## 1 ARID2
## 2 KEAP1
## 3 KRAS
## 4 TP53
## 5 MGA
## 6 COL2A1
## # … with 1 more row
## #
## # Edge Data: 6 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 3 1 0.25
## 2 2 1 1 1
## 3 2 3 1 0.25
## # … with 3 more rows
##
## $fit$clones_to_expand$CRUK0020$`2`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 PIK3CA
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0020$`3`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 BAP1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0020$`4`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 NCOR1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0021
## $fit$clones_to_expand$CRUK0021$`1`
## # A tbl_graph: 4 nodes and 2 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 4 x 1 (active)
## cluster
## <chr>
## 1 CDKN2A
## 2 EGFR
## 3 TP53
## 4 CHEK2
## #
## # Edge Data: 2 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 3 1 0.5
## 2 2 3 1 0.5
##
##
## $fit$clones_to_expand$CRUK0022
## $fit$clones_to_expand$CRUK0022$`1`
## # A tbl_graph: 2 nodes and 1 edges
## #
## # A rooted tree
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 EGFR
## 2 TP53
## #
## # Edge Data: 1 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
##
## $fit$clones_to_expand$CRUK0022$`2`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 CIC
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0023
## $fit$clones_to_expand$CRUK0023$`1`
## # A tbl_graph: 3 nodes and 0 edges
## #
## # A rooted forest with 3 trees
## #
## # Node Data: 3 x 1 (active)
## cluster
## <chr>
## 1 WRN
## 2 KRAS
## 3 CDKN2A
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0023$`2`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 TP53
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0023$`4`
## # A tbl_graph: 2 nodes and 0 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 PTPRC
## 2 KMT2D
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0024
## $fit$clones_to_expand$CRUK0024$`1`
## # A tbl_graph: 4 nodes and 2 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 4 x 1 (active)
## cluster
## <chr>
## 1 EGFR
## 2 STK11
## 3 TP53
## 4 POLE
## #
## # Edge Data: 2 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 3 1 1
## 2 2 1 1 1
##
## $fit$clones_to_expand$CRUK0024$`3`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 ATM
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0024$`4`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 NCOR1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0025
## $fit$clones_to_expand$CRUK0025$`1`
## # A tbl_graph: 3 nodes and 3 edges
## #
## # A directed simple graph with 1 component
## #
## # Node Data: 3 x 1 (active)
## cluster
## <chr>
## 1 KRAS
## 2 TP53
## 3 MGA
## #
## # Edge Data: 3 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 3 1 1
## 2 1 2 1 1
## 3 2 1 2 1
##
##
## $fit$clones_to_expand$CRUK0026
## $fit$clones_to_expand$CRUK0026$`1`
## # A tbl_graph: 4 nodes and 2 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 4 x 1 (active)
## cluster
## <chr>
## 1 EGFR
## 2 TP53
## 3 RB1
## 4 SERPINB13
## #
## # Edge Data: 2 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 3 1 1
## 2 1 2 1 1
##
##
## $fit$clones_to_expand$CRUK0027
## $fit$clones_to_expand$CRUK0027$`1`
## # A tbl_graph: 2 nodes and 2 edges
## #
## # A directed simple graph with 1 component
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 KRAS
## 2 TP53
## #
## # Edge Data: 2 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
## 2 2 1 2 1
##
## $fit$clones_to_expand$CRUK0027$`2`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 PLXNB2
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0028
## $fit$clones_to_expand$CRUK0028$`1`
## # A tbl_graph: 2 nodes and 0 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 APC
## 2 EGFR
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0029
## $fit$clones_to_expand$CRUK0029$`1`
## # A tbl_graph: 4 nodes and 1 edges
## #
## # A rooted forest with 3 trees
## #
## # Node Data: 4 x 1 (active)
## cluster
## <chr>
## 1 TP53
## 2 NRAS
## 3 MGA
## 4 CCND1
## #
## # Edge Data: 1 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
##
##
## $fit$clones_to_expand$CRUK0030
## $fit$clones_to_expand$CRUK0030$`1`
## # A tbl_graph: 6 nodes and 3 edges
## #
## # A directed simple graph with 4 components
## #
## # Node Data: 6 x 1 (active)
## cluster
## <chr>
## 1 KRAS
## 2 TP53
## 3 TSC2
## 4 U2AF1
## 5 FBXW7
## 6 NF1
## #
## # Edge Data: 3 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
## 2 2 1 2 1
## 3 2 6 1 1
##
##
## $fit$clones_to_expand$CRUK0031
## $fit$clones_to_expand$CRUK0031$`1`
## # A tbl_graph: 4 nodes and 0 edges
## #
## # A rooted forest with 4 trees
## #
## # Node Data: 4 x 1 (active)
## cluster
## <chr>
## 1 KEAP1
## 2 CDKN2A
## 3 PRF1
## 4 FGFR1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0031$`6`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 NF1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0032
## $fit$clones_to_expand$CRUK0032$`1`
## # A tbl_graph: 4 nodes and 0 edges
## #
## # A rooted forest with 4 trees
## #
## # Node Data: 4 x 1 (active)
## cluster
## <chr>
## 1 ATM
## 2 RAD21
## 3 U2AF1
## 4 RNF43
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0032$`4`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 CCND1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0032$`6`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 ARID1B
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0033
## $fit$clones_to_expand$CRUK0033$`1`
## # A tbl_graph: 2 nodes and 0 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 KEAP1
## 2 CTNNB1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0034
## $fit$clones_to_expand$CRUK0034$`1`
## # A tbl_graph: 3 nodes and 1 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 3 x 1 (active)
## cluster
## <chr>
## 1 KRAS
## 2 ATM
## 3 PLXNB2
## #
## # Edge Data: 1 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 3 1 1
##
## $fit$clones_to_expand$CRUK0034$`4`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 MGA
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0035
## $fit$clones_to_expand$CRUK0035$`1`
## # A tbl_graph: 2 nodes and 1 edges
## #
## # A rooted tree
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 TP53
## 2 FAS
## #
## # Edge Data: 1 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
##
## $fit$clones_to_expand$CRUK0035$`4`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 FLT4
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0036
## $fit$clones_to_expand$CRUK0036$`1`
## # A tbl_graph: 5 nodes and 4 edges
## #
## # A rooted tree
## #
## # Node Data: 5 x 1 (active)
## cluster
## <chr>
## 1 ARHGAP35
## 2 KEAP1
## 3 PIK3CA
## 4 TERT
## 5 KRAS
## #
## # Edge Data: 4 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 4 1 0.5
## 2 2 5 1 0.5
## 3 3 4 1 0.5
## # … with 1 more row
##
##
## $fit$clones_to_expand$CRUK0037
## $fit$clones_to_expand$CRUK0037$`1`
## # A tbl_graph: 3 nodes and 0 edges
## #
## # A rooted forest with 3 trees
## #
## # Node Data: 3 x 1 (active)
## cluster
## <chr>
## 1 NCOA6
## 2 CREBBP
## 3 KRAS
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0038
## $fit$clones_to_expand$CRUK0038$`1`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 KRAS
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0038$`3`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 KMT2D
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0039
## $fit$clones_to_expand$CRUK0039$`1`
## # A tbl_graph: 4 nodes and 0 edges
## #
## # A rooted forest with 4 trees
## #
## # Node Data: 4 x 1 (active)
## cluster
## <chr>
## 1 KRAS
## 2 CMTR2
## 3 NF1
## 4 PHOX2B
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0040
## $fit$clones_to_expand$CRUK0040$`1`
## # A tbl_graph: 4 nodes and 1 edges
## #
## # A rooted forest with 3 trees
## #
## # Node Data: 4 x 1 (active)
## cluster
## <chr>
## 1 KRAS
## 2 NCOR1
## 3 RAD21
## 4 GATA3
## #
## # Edge Data: 1 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
##
##
## $fit$clones_to_expand$CRUK0041
## $fit$clones_to_expand$CRUK0041$`1`
## # A tbl_graph: 3 nodes and 1 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 3 x 1 (active)
## cluster
## <chr>
## 1 BRAF
## 2 TERT
## 3 EGFR
## #
## # Edge Data: 1 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
##
##
## $fit$clones_to_expand$CRUK0042
## $fit$clones_to_expand$CRUK0042$`1`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 KRAS
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0043
## $fit$clones_to_expand$CRUK0043$`1`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 MET
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0044
## $fit$clones_to_expand$CRUK0044$`1`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 KRAS
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0045
## $fit$clones_to_expand$CRUK0045$`1`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 BAP1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0046
## $fit$clones_to_expand$CRUK0046$`1`
## # A tbl_graph: 2 nodes and 0 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 KEAP1
## 2 APC
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0047
## $fit$clones_to_expand$CRUK0047$`1`
## # A tbl_graph: 4 nodes and 2 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 4 x 1 (active)
## cluster
## <chr>
## 1 MYC
## 2 STK11
## 3 APC
## 4 KRAS
## #
## # Edge Data: 2 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 4 1 0.5
## 2 2 4 1 0.5
##
##
## $fit$clones_to_expand$CRUK0048
## $fit$clones_to_expand$CRUK0048$`1`
## # A tbl_graph: 7 nodes and 3 edges
## #
## # A directed acyclic simple graph with 5 components
## #
## # Node Data: 7 x 1 (active)
## cluster
## <chr>
## 1 EGFR
## 2 TP53
## 3 APC
## 4 PRDM1
## 5 ARHGAP35
## 6 BRAF
## # … with 1 more row
## #
## # Edge Data: 3 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 5 1 0.5
## 2 1 2 1 1
## 3 2 5 1 0.5
##
##
## $fit$clones_to_expand$CRUK0049
## $fit$clones_to_expand$CRUK0049$`1`
## # A tbl_graph: 5 nodes and 4 edges
## #
## # A directed simple graph with 2 components
## #
## # Node Data: 5 x 1 (active)
## cluster
## <chr>
## 1 EGFR
## 2 KRAS
## 3 TP53
## 4 RB1
## 5 COL2A1
## #
## # Edge Data: 4 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 4 1 1
## 2 1 3 1 0.5
## 3 2 3 1 0.5
## # … with 1 more row
##
##
## $fit$clones_to_expand$CRUK0050
## $fit$clones_to_expand$CRUK0050$`1`
## # A tbl_graph: 3 nodes and 2 edges
## #
## # A rooted tree
## #
## # Node Data: 3 x 1 (active)
## cluster
## <chr>
## 1 MYC
## 2 STK11
## 3 KRAS
## #
## # Edge Data: 2 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 3 1 0.5
## 2 2 3 1 0.5
##
##
## $fit$clones_to_expand$CRUK0051
## $fit$clones_to_expand$CRUK0051$`1`
## # A tbl_graph: 4 nodes and 3 edges
## #
## # A directed simple graph with 2 components
## #
## # Node Data: 4 x 1 (active)
## cluster
## <chr>
## 1 EGFR
## 2 KRAS
## 3 TP53
## 4 FBXW7
## #
## # Edge Data: 3 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 3 1 0.5
## 2 2 3 1 0.5
## 3 3 2 2 1
##
## $fit$clones_to_expand$CRUK0051$`3`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 EP300
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0052
## $fit$clones_to_expand$CRUK0052$`1`
## # A tbl_graph: 8 nodes and 8 edges
## #
## # A directed simple graph with 3 components
## #
## # Node Data: 8 x 1 (active)
## cluster
## <chr>
## 1 KEAP1
## 2 KRAS
## 3 MGA
## 4 TP53
## 5 KMT2D
## 6 NOTCH2
## # … with 2 more rows
## #
## # Edge Data: 8 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 0.333
## 2 1 7 1 0.333
## 3 2 5 2 1
## # … with 5 more rows
##
## $fit$clones_to_expand$CRUK0052$`2`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 UBR5
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0054
## $fit$clones_to_expand$CRUK0054$`1`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 EGFR
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0055
## $fit$clones_to_expand$CRUK0055$`1`
## # A tbl_graph: 2 nodes and 0 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 FANCM
## 2 UBR5
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0055$`2`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 FAT1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0056
## $fit$clones_to_expand$CRUK0056$`1`
## # A tbl_graph: 2 nodes and 0 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 RASA1
## 2 CREBBP
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0056$`3`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 TP53
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0057
## $fit$clones_to_expand$CRUK0057$`1`
## # A tbl_graph: 5 nodes and 2 edges
## #
## # A rooted forest with 3 trees
## #
## # Node Data: 5 x 1 (active)
## cluster
## <chr>
## 1 TERT
## 2 KRAS
## 3 SMARCA4
## 4 TSC2
## 5 DNM2
## #
## # Edge Data: 2 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 5 1 1
## 2 1 2 1 1
##
##
## $fit$clones_to_expand$CRUK0058
## $fit$clones_to_expand$CRUK0058$`1`
## # A tbl_graph: 2 nodes and 1 edges
## #
## # A rooted tree
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 EGFR
## 2 TP53
## #
## # Edge Data: 1 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
##
##
## $fit$clones_to_expand$CRUK0059
## $fit$clones_to_expand$CRUK0059$`1`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 KRAS
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0060
## $fit$clones_to_expand$CRUK0060$`1`
## # A tbl_graph: 11 nodes and 3 edges
## #
## # A rooted forest with 8 trees
## #
## # Node Data: 11 x 1 (active)
## cluster
## <chr>
## 1 NCOA6
## 2 NF1
## 3 SERPINB13
## 4 ARID2
## 5 COL5A2
## 6 FANCM
## # … with 5 more rows
## #
## # Edge Data: 3 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 5 1 0.5
## 2 2 6 1 1
## 3 3 5 1 0.5
##
##
## $fit$clones_to_expand$CRUK0061
## $fit$clones_to_expand$CRUK0061$`1`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 STK11
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0062
## $fit$clones_to_expand$CRUK0062$`1`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 FAS
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0062$`2`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 PLXNB2
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0062$`4`
## # A tbl_graph: 4 nodes and 0 edges
## #
## # A rooted forest with 4 trees
## #
## # Node Data: 4 x 1 (active)
## cluster
## <chr>
## 1 TP53
## 2 PIK3CA
## 3 SOX2
## 4 CCND1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0062$`16`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 UBR5
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0063
## $fit$clones_to_expand$CRUK0063$`1`
## # A tbl_graph: 2 nodes and 0 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 NF1
## 2 CYLD
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0063$`2`
## # A tbl_graph: 7 nodes and 4 edges
## #
## # A rooted forest with 3 trees
## #
## # Node Data: 7 x 1 (active)
## cluster
## <chr>
## 1 CDKN2A
## 2 PIK3CA
## 3 SOX2
## 4 TP53
## 5 FBXW7
## 6 TERT
## # … with 1 more row
## #
## # Edge Data: 4 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 4 1 1
## 2 2 6 1 0.25
## 3 3 6 1 0.25
## # … with 1 more row
##
## $fit$clones_to_expand$CRUK0063$`6`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 FANCM
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0063$`10`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 EP300
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0064
## $fit$clones_to_expand$CRUK0064$`1`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 TP53
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0064$`2`
## # A tbl_graph: 2 nodes and 0 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 MLH1
## 2 FAT1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0065
## $fit$clones_to_expand$CRUK0065$`1`
## # A tbl_graph: 4 nodes and 3 edges
## #
## # A rooted tree
## #
## # Node Data: 4 x 1 (active)
## cluster
## <chr>
## 1 PIK3CA
## 2 SOX2
## 3 TP53
## 4 NFE2L2
## #
## # Edge Data: 3 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 4 2 0.286
## 2 2 4 2 0.286
## 3 3 4 3 0.429
##
## $fit$clones_to_expand$CRUK0065$`2`
## # A tbl_graph: 3 nodes and 0 edges
## #
## # A rooted forest with 3 trees
## #
## # Node Data: 3 x 1 (active)
## cluster
## <chr>
## 1 MLH1
## 2 PTPRC
## 3 UBR5
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0065$`6`
## # A tbl_graph: 2 nodes and 0 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 NOTCH1
## 2 NCOA6
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0066
## $fit$clones_to_expand$CRUK0066$`1`
## # A tbl_graph: 7 nodes and 5 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 7 x 1 (active)
## cluster
## <chr>
## 1 CDKN2A
## 2 TP53
## 3 WRN
## 4 NOTCH1
## 5 PDGFRA
## 6 TERT
## # … with 1 more row
## #
## # Edge Data: 5 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 0.5
## 2 2 7 1 1
## 3 2 4 2 1
## # … with 2 more rows
##
## $fit$clones_to_expand$CRUK0066$`9`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 COL5A2
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0067
## $fit$clones_to_expand$CRUK0067$`1`
## # A tbl_graph: 5 nodes and 4 edges
## #
## # A rooted tree
## #
## # Node Data: 5 x 1 (active)
## cluster
## <chr>
## 1 CDKN2A
## 2 PIK3CA
## 3 SOX2
## 4 TP53
## 5 NOTCH1
## #
## # Edge Data: 4 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 4 1 1
## 2 2 5 1 0.25
## 3 3 5 1 0.25
## # … with 1 more row
##
## $fit$clones_to_expand$CRUK0067$`2`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 NFE2L2
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0068
## $fit$clones_to_expand$CRUK0068$`1`
## # A tbl_graph: 5 nodes and 0 edges
## #
## # A rooted forest with 5 trees
## #
## # Node Data: 5 x 1 (active)
## cluster
## <chr>
## 1 TP53
## 2 PTEN
## 3 KMT2D
## 4 PIK3CA
## 5 SOX2
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0068$`3`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 MGA
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0068$`4`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 SETD2
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0068$`9`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 TERT
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0069
## $fit$clones_to_expand$CRUK0069$`1`
## # A tbl_graph: 4 nodes and 1 edges
## #
## # A rooted forest with 3 trees
## #
## # Node Data: 4 x 1 (active)
## cluster
## <chr>
## 1 TP53
## 2 FAT1
## 3 PDGFRA
## 4 FGFR1
## #
## # Edge Data: 1 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
##
## $fit$clones_to_expand$CRUK0069$`13`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 KRAS
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0070
## $fit$clones_to_expand$CRUK0070$`1`
## # A tbl_graph: 4 nodes and 3 edges
## #
## # A rooted tree
## #
## # Node Data: 4 x 1 (active)
## cluster
## <chr>
## 1 SOX2
## 2 TP53
## 3 DNM2
## 4 COL5A2
## #
## # Edge Data: 3 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 4 1 0.333
## 2 2 4 2 0.667
## 3 2 3 1 1
##
## $fit$clones_to_expand$CRUK0070$`2`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 CBLB
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0070$`3`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 NFE2L2
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0071
## $fit$clones_to_expand$CRUK0071$`1`
## # A tbl_graph: 3 nodes and 0 edges
## #
## # A rooted forest with 3 trees
## #
## # Node Data: 3 x 1 (active)
## cluster
## <chr>
## 1 CMTR2
## 2 PIK3CA
## 3 SOX2
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0071$`4`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 UBR5
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0072
## $fit$clones_to_expand$CRUK0072$`1`
## # A tbl_graph: 6 nodes and 4 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 6 x 1 (active)
## cluster
## <chr>
## 1 EGFR
## 2 PIK3CA
## 3 SOX2
## 4 TP53
## 5 NFE2L2
## 6 MYC
## #
## # Edge Data: 4 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 4 1 1
## 2 2 5 2 0.286
## 3 3 5 2 0.286
## # … with 1 more row
##
##
## $fit$clones_to_expand$CRUK0073
## $fit$clones_to_expand$CRUK0073$`1`
## # A tbl_graph: 8 nodes and 4 edges
## #
## # A rooted forest with 4 trees
## #
## # Node Data: 8 x 1 (active)
## cluster
## <chr>
## 1 CDKN2A
## 2 FAT1
## 3 FGFR1
## 4 DICER1
## 5 NFE2L2
## 6 KMT2D
## # … with 2 more rows
## #
## # Edge Data: 4 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 6 1 1
## 2 1 5 1 0.333
## 3 2 5 1 0.333
## # … with 1 more row
##
## $fit$clones_to_expand$CRUK0073$`2`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 PLXNB2
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0074
## $fit$clones_to_expand$CRUK0074$`1`
## # A tbl_graph: 5 nodes and 3 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 5 x 1 (active)
## cluster
## <chr>
## 1 PIK3CA
## 2 SOX2
## 3 TP53
## 4 NFE2L2
## 5 CCND1
## #
## # Edge Data: 3 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 4 2 0.286
## 2 2 4 2 0.286
## 3 3 4 3 0.429
##
## $fit$clones_to_expand$CRUK0074$`3`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 UBR5
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0075
## $fit$clones_to_expand$CRUK0075$`1`
## # A tbl_graph: 7 nodes and 4 edges
## #
## # A rooted forest with 3 trees
## #
## # Node Data: 7 x 1 (active)
## cluster
## <chr>
## 1 PIK3CA
## 2 RASA1
## 3 TP53
## 4 NOTCH1
## 5 FAT1
## 6 MGA
## # … with 1 more row
## #
## # Edge Data: 4 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 4 1 0.333
## 2 2 3 1 1
## 3 3 5 1 1
## # … with 1 more row
##
## $fit$clones_to_expand$CRUK0075$`2`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 NFE2L2
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0076
## $fit$clones_to_expand$CRUK0076$`1`
## # A tbl_graph: 6 nodes and 1 edges
## #
## # A rooted forest with 5 trees
## #
## # Node Data: 6 x 1 (active)
## cluster
## <chr>
## 1 TP53
## 2 SERPINB13
## 3 ARID1B
## 4 PIK3CA
## 5 SOX2
## 6 FGFR1
## #
## # Edge Data: 1 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 3 1 1
##
## $fit$clones_to_expand$CRUK0076$`2`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 NCOR1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0076$`3`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 COL5A2
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0077
## $fit$clones_to_expand$CRUK0077$`1`
## # A tbl_graph: 3 nodes and 1 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 3 x 1 (active)
## cluster
## <chr>
## 1 TP53
## 2 LATS1
## 3 KEAP1
## #
## # Edge Data: 1 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
##
##
## $fit$clones_to_expand$CRUK0078
## $fit$clones_to_expand$CRUK0078$`1`
## # A tbl_graph: 5 nodes and 1 edges
## #
## # A rooted forest with 4 trees
## #
## # Node Data: 5 x 1 (active)
## cluster
## <chr>
## 1 FGFR1
## 2 PLXNB2
## 3 PTEN
## 4 PIK3CA
## 5 SOX2
## #
## # Edge Data: 1 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
##
##
## $fit$clones_to_expand$CRUK0079
## $fit$clones_to_expand$CRUK0079$`1`
## # A tbl_graph: 6 nodes and 1 edges
## #
## # A rooted forest with 5 trees
## #
## # Node Data: 6 x 1 (active)
## cluster
## <chr>
## 1 TP53
## 2 FAT1
## 3 POLE
## 4 PIK3CA
## 5 SOX2
## 6 FGFR1
## #
## # Edge Data: 1 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
##
##
## $fit$clones_to_expand$CRUK0080
## $fit$clones_to_expand$CRUK0080$`1`
## # A tbl_graph: 4 nodes and 1 edges
## #
## # A rooted forest with 3 trees
## #
## # Node Data: 4 x 1 (active)
## cluster
## <chr>
## 1 EGFR
## 2 TP53
## 3 WT1
## 4 CCND1
## #
## # Edge Data: 1 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
##
## $fit$clones_to_expand$CRUK0080$`3`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 IKZF1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0081
## $fit$clones_to_expand$CRUK0081$`1`
## # A tbl_graph: 5 nodes and 4 edges
## #
## # A rooted tree
## #
## # Node Data: 5 x 1 (active)
## cluster
## <chr>
## 1 CDKN2A
## 2 TP53
## 3 NOTCH1
## 4 FAT1
## 5 FANCC
## #
## # Edge Data: 4 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
## 2 2 5 1 1
## 3 2 4 1 1
## # … with 1 more row
##
## $fit$clones_to_expand$CRUK0081$`3`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 CYLD
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0082
## $fit$clones_to_expand$CRUK0082$`1`
## # A tbl_graph: 8 nodes and 4 edges
## #
## # A rooted forest with 4 trees
## #
## # Node Data: 8 x 1 (active)
## cluster
## <chr>
## 1 FGFR1
## 2 PIK3CA
## 3 SOX2
## 4 TP53
## 5 WT1
## 6 PTEN
## # … with 2 more rows
## #
## # Edge Data: 4 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 7 1 0.2
## 2 2 7 1 0.2
## 3 3 7 1 0.2
## # … with 1 more row
##
##
## $fit$clones_to_expand$CRUK0083
## $fit$clones_to_expand$CRUK0083$`1`
## # A tbl_graph: 7 nodes and 1 edges
## #
## # A rooted forest with 6 trees
## #
## # Node Data: 7 x 1 (active)
## cluster
## <chr>
## 1 RASA1
## 2 TP53
## 3 FBXW7
## 4 PIK3CA
## 5 SOX2
## 6 FGFR1
## # … with 1 more row
## #
## # Edge Data: 1 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
##
##
## $fit$clones_to_expand$CRUK0084
## $fit$clones_to_expand$CRUK0084$`1`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 CREBBP
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0085
## $fit$clones_to_expand$CRUK0085$`1`
## # A tbl_graph: 4 nodes and 0 edges
## #
## # A rooted forest with 4 trees
## #
## # Node Data: 4 x 1 (active)
## cluster
## <chr>
## 1 CHEK2
## 2 CREBBP
## 3 LATS1
## 4 FANCM
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0086
## $fit$clones_to_expand$CRUK0086$`1`
## # A tbl_graph: 3 nodes and 1 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 3 x 1 (active)
## cluster
## <chr>
## 1 TP53
## 2 ARID2
## 3 FAT1
## #
## # Edge Data: 1 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 3 1 1
##
##
## $fit$clones_to_expand$CRUK0087
## $fit$clones_to_expand$CRUK0087$`1`
## # A tbl_graph: 4 nodes and 2 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 4 x 1 (active)
## cluster
## <chr>
## 1 PIK3CA
## 2 TP53
## 3 NFE2L2
## 4 ASXL1
## #
## # Edge Data: 2 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 3 2 0.4
## 2 2 3 3 0.6
##
##
## $fit$clones_to_expand$CRUK0088
## $fit$clones_to_expand$CRUK0088$`1`
## # A tbl_graph: 2 nodes and 0 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 CUX1
## 2 TP53
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0089
## $fit$clones_to_expand$CRUK0089$`1`
## # A tbl_graph: 3 nodes and 0 edges
## #
## # A rooted forest with 3 trees
## #
## # Node Data: 3 x 1 (active)
## cluster
## <chr>
## 1 PIK3CA
## 2 SMAD4
## 3 KEAP1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0090
## $fit$clones_to_expand$CRUK0090$`1`
## # A tbl_graph: 5 nodes and 0 edges
## #
## # A rooted forest with 5 trees
## #
## # Node Data: 5 x 1 (active)
## cluster
## <chr>
## 1 CDKN2A
## 2 NCOA6
## 3 CUX1
## 4 COL2A1
## 5 NRAS
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0091
## $fit$clones_to_expand$CRUK0091$`1`
## # A tbl_graph: 3 nodes and 1 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 3 x 1 (active)
## cluster
## <chr>
## 1 CDKN2A
## 2 TP53
## 3 SMARCA4
## #
## # Edge Data: 1 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
##
##
## $fit$clones_to_expand$CRUK0092
## $fit$clones_to_expand$CRUK0092$`1`
## # A tbl_graph: 5 nodes and 3 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 5 x 1 (active)
## cluster
## <chr>
## 1 RASA1
## 2 TP53
## 3 SMAD4
## 4 CBLB
## 5 PIK3CA
## #
## # Edge Data: 3 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
## 2 2 4 1 1
## 3 2 3 1 1
##
##
## $fit$clones_to_expand$CRUK0093
## $fit$clones_to_expand$CRUK0093$`1`
## # A tbl_graph: 7 nodes and 4 edges
## #
## # A directed acyclic simple graph with 4 components
## #
## # Node Data: 7 x 1 (active)
## cluster
## <chr>
## 1 CDKN2A
## 2 TP53
## 3 DICER1
## 4 COL2A1
## 5 GATA3
## 6 CIC
## # … with 1 more row
## #
## # Edge Data: 4 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 7 1 0.333
## 2 1 2 1 1
## 3 2 6 1 1
## # … with 1 more row
##
##
## $fit$clones_to_expand$CRUK0094
## $fit$clones_to_expand$CRUK0094$`1`
## # A tbl_graph: 2 nodes and 0 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 SMARCA4
## 2 TERT
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0095
## $fit$clones_to_expand$CRUK0095$`1`
## # A tbl_graph: 3 nodes and 2 edges
## #
## # A rooted tree
## #
## # Node Data: 3 x 1 (active)
## cluster
## <chr>
## 1 RASA1
## 2 TP53
## 3 NF1
## #
## # Edge Data: 2 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 2 1 1
## 2 2 3 1 1
##
##
## $fit$clones_to_expand$CRUK0096
## $fit$clones_to_expand$CRUK0096$`1`
## # A tbl_graph: 3 nodes and 0 edges
## #
## # A rooted forest with 3 trees
## #
## # Node Data: 3 x 1 (active)
## cluster
## <chr>
## 1 KRAS
## 2 SGK223
## 3 MAP3K1
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0097
## $fit$clones_to_expand$CRUK0097$`1`
## # A tbl_graph: 2 nodes and 0 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 TP53
## 2 PTEN
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0098
## $fit$clones_to_expand$CRUK0098$`1`
## # A tbl_graph: 2 nodes and 0 edges
## #
## # A rooted forest with 2 trees
## #
## # Node Data: 2 x 1 (active)
## cluster
## <chr>
## 1 TP53
## 2 PTEN
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
## $fit$clones_to_expand$CRUK0098$`3`
## # A tbl_graph: 1 nodes and 0 edges
## #
## # A rooted tree
## #
## # Node Data: 1 x 1 (active)
## cluster
## <chr>
## 1 UBR5
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0099
## $fit$clones_to_expand$CRUK0099$`1`
## # A tbl_graph: 3 nodes and 0 edges
## #
## # A rooted forest with 3 trees
## #
## # Node Data: 3 x 1 (active)
## cluster
## <chr>
## 1 STK11
## 2 KEAP1
## 3 TP53
## #
## # Edge Data: 0 x 4
## # … with 4 variables: from <int>, to <int>, count <int>, penalty <dbl>
##
##
## $fit$clones_to_expand$CRUK0100
## $fit$clones_to_expand$CRUK0100$`1`
## # A tbl_graph: 6 nodes and 3 edges
## #
## # A directed acyclic simple graph with 4 components
## #
## # Node Data: 6 x 1 (active)
## cluster
## <chr>
## 1 CDKN2A
## 2 TP53
## 3 PHOX2B
## 4 COL5A2
## 5 STK11
## 6 SPEN
## #
## # Edge Data: 3 x 4
## from to count penalty
## <int> <int> <int> <dbl>
## 1 1 4 1 0.333
## 2 1 2 1 1
## 3 2 4 2 0.667
##
##
##
## $fit$clones_expansions
## $fit$clones_expansions$CRUK0001
## # A tibble: 10 x 2
## from to
## <chr> <chr>
## 1 GL EGFR
## 2 GL WRN
## 3 GL MGA
## 4 EGFR TP53
## 5 WRN TP53
## 6 TP53 NF1
## 7 MGA NF1
## 8 TP53 ARHGAP35
## 9 MGA ARHGAP35
## 10 NF1 PASK
##
## $fit$clones_expansions$CRUK0002
## # A tibble: 7 x 2
## from to
## <chr> <chr>
## 1 GL MET
## 2 MET TERT
## 3 TERT EP300
## 4 TERT RB1
## 5 TERT IKZF1
## 6 TERT KRAS
## 7 EP300 NF1
##
## $fit$clones_expansions$CRUK0003
## # A tibble: 6 x 2
## from to
## <chr> <chr>
## 1 GL PIK3CA
## 2 GL EGFR
## 3 GL CDKN2A
## 4 PIK3CA CTNNB1
## 5 EGFR CTNNB1
## 6 CDKN2A CTNNB1
##
## $fit$clones_expansions$CRUK0004
## # A tibble: 4 x 2
## from to
## <chr> <chr>
## 1 GL EGFR
## 2 EGFR TP53
## 3 TP53 SMAD4
## 4 TP53 NOTCH1
##
## $fit$clones_expansions$CRUK0005
## # A tibble: 9 x 2
## from to
## <chr> <chr>
## 1 GL BRAF
## 2 GL TP53
## 3 GL CMTR2
## 4 GL PASK
## 5 BRAF TERT
## 6 TP53 TERT
## 7 CMTR2 NRAS
## 8 PASK NRAS
## 9 TERT NRAS
##
## $fit$clones_expansions$CRUK0006
## # A tibble: 10 x 2
## from to
## <chr> <chr>
## 1 GL TP53
## 2 GL KEAP1
## 3 TP53 PLXNB2
## 4 TP53 TERT
## 5 PLXNB2 MAP3K1
## 6 KEAP1 MAP3K1
## 7 TERT MAP3K1
## 8 PLXNB2 FANCC
## 9 KEAP1 FANCC
## 10 TERT FANCC
##
## $fit$clones_expansions$CRUK0007
## # A tibble: 3 x 2
## from to
## <chr> <chr>
## 1 GL PIK3CA
## 2 GL EGFR
## 3 GL SGK223
##
## $fit$clones_expansions$CRUK0008
## # A tibble: 10 x 2
## from to
## <chr> <chr>
## 1 GL KEAP1
## 2 GL STK11
## 3 GL PRDM1
## 4 GL U2AF1
## 5 GL MYC
## 6 KEAP1 ARID2
## 7 STK11 ARID2
## 8 PRDM1 ARID2
## 9 U2AF1 ARID2
## 10 MYC ARID2
##
## $fit$clones_expansions$CRUK0009
## # A tibble: 11 x 2
## from to
## <chr> <chr>
## 1 GL TP53
## 2 GL BRAF
## 3 GL KMT2C
## 4 GL MET
## 5 TP53 ARHGAP35
## 6 TP53 NFE2L2
## 7 BRAF TERT
## 8 ARHGAP35 TERT
## 9 KMT2C TERT
## 10 NFE2L2 TERT
## 11 MET TERT
##
## $fit$clones_expansions$CRUK0010
## # A tibble: 3 x 2
## from to
## <chr> <chr>
## 1 GL SETD2
## 2 GL EGFR
## 3 GL TERT
##
## $fit$clones_expansions$CRUK0011
## # A tibble: 2 x 2
## from to
## <chr> <chr>
## 1 GL KRAS
## 2 KRAS FLT4
##
## $fit$clones_expansions$CRUK0012
## # A tibble: 1 x 2
## from to
## <chr> <chr>
## 1 GL EGFR
##
## $fit$clones_expansions$CRUK0013
## # A tibble: 4 x 2
## from to
## <chr> <chr>
## 1 GL STK11
## 2 STK11 NOTCH1
## 3 STK11 KRAS
## 4 STK11 EGFR
##
## $fit$clones_expansions$CRUK0014
## # A tibble: 6 x 2
## from to
## <chr> <chr>
## 1 GL KRAS
## 2 GL TP53
## 3 KRAS TP53
## 4 TP53 KRAS
## 5 KRAS RNF43
## 6 TP53 RNF43
##
## $fit$clones_expansions$CRUK0015
## # A tibble: 6 x 2
## from to
## <chr> <chr>
## 1 GL BAP1
## 2 GL EGFR
## 3 BAP1 TP53
## 4 EGFR TP53
## 5 BAP1 RB1
## 6 EGFR RB1
##
## $fit$clones_expansions$CRUK0016
## # A tibble: 24 x 2
## from to
## <chr> <chr>
## 1 GL CDKN2A
## 2 GL SPEN
## 3 CDKN2A TP53
## 4 TP53 FAT1
## 5 TP53 CBLB
## 6 TP53 TERT
## 7 FAT1 LATS1
## 8 SPEN LATS1
## 9 CBLB LATS1
## 10 TERT LATS1
## # … with 14 more rows
##
## $fit$clones_expansions$CRUK0017
## # A tibble: 8 x 2
## from to
## <chr> <chr>
## 1 GL KEAP1
## 2 GL MYC
## 3 GL TP53
## 4 KEAP1 ARID2
## 5 MYC ARID2
## 6 TP53 ARID1B
## 7 ARID1B KRAS
## 8 ARID2 KRAS
##
## $fit$clones_expansions$CRUK0018
## # A tibble: 4 x 2
## from to
## <chr> <chr>
## 1 GL KRAS
## 2 GL CMTR2
## 3 GL COL5A2
## 4 KRAS MGA
##
## $fit$clones_expansions$CRUK0019
## # A tibble: 1 x 2
## from to
## <chr> <chr>
## 1 GL EGFR
##
## $fit$clones_expansions$CRUK0020
## # A tibble: 22 x 2
## from to
## <chr> <chr>
## 1 GL KEAP1
## 2 GL COL2A1
## 3 GL PRF1
## 4 GL KRAS
## 5 GL TP53
## 6 ARID2 KRAS
## 7 KEAP1 ARID2
## 8 KEAP1 KRAS
## 9 KRAS TP53
## 10 KRAS MGA
## # … with 12 more rows
##
## $fit$clones_expansions$CRUK0021
## # A tibble: 5 x 2
## from to
## <chr> <chr>
## 1 GL CDKN2A
## 2 GL EGFR
## 3 GL CHEK2
## 4 CDKN2A TP53
## 5 EGFR TP53
##
## $fit$clones_expansions$CRUK0022
## # A tibble: 3 x 2
## from to
## <chr> <chr>
## 1 GL EGFR
## 2 EGFR TP53
## 3 TP53 CIC
##
## $fit$clones_expansions$CRUK0023
## # A tibble: 12 x 2
## from to
## <chr> <chr>
## 1 GL WRN
## 2 GL KRAS
## 3 GL CDKN2A
## 4 WRN PTPRC
## 5 KRAS PTPRC
## 6 CDKN2A PTPRC
## 7 WRN KMT2D
## 8 KRAS KMT2D
## 9 CDKN2A KMT2D
## 10 WRN TP53
## 11 KRAS TP53
## 12 CDKN2A TP53
##
## $fit$clones_expansions$CRUK0024
## # A tibble: 7 x 2
## from to
## <chr> <chr>
## 1 GL STK11
## 2 GL POLE
## 3 EGFR TP53
## 4 STK11 EGFR
## 5 TP53 ATM
## 6 POLE ATM
## 7 ATM NCOR1
##
## $fit$clones_expansions$CRUK0025
## # A tibble: 5 x 2
## from to
## <chr> <chr>
## 1 GL KRAS
## 2 GL TP53
## 3 KRAS TP53
## 4 KRAS MGA
## 5 TP53 KRAS
##
## $fit$clones_expansions$CRUK0026
## # A tibble: 4 x 2
## from to
## <chr> <chr>
## 1 GL EGFR
## 2 GL SERPINB13
## 3 EGFR TP53
## 4 EGFR RB1
##
## $fit$clones_expansions$CRUK0027
## # A tibble: 6 x 2
## from to
## <chr> <chr>
## 1 GL KRAS
## 2 GL TP53
## 3 KRAS TP53
## 4 TP53 KRAS
## 5 KRAS PLXNB2
## 6 TP53 PLXNB2
##
## $fit$clones_expansions$CRUK0028
## # A tibble: 2 x 2
## from to
## <chr> <chr>
## 1 GL APC
## 2 GL EGFR
##
## $fit$clones_expansions$CRUK0029
## # A tibble: 4 x 2
## from to
## <chr> <chr>
## 1 GL TP53
## 2 GL MGA
## 3 GL CCND1
## 4 TP53 NRAS
##
## $fit$clones_expansions$CRUK0030
## # A tibble: 8 x 2
## from to
## <chr> <chr>
## 1 GL TSC2
## 2 GL U2AF1
## 3 GL FBXW7
## 4 GL KRAS
## 5 GL TP53
## 6 KRAS TP53
## 7 TP53 KRAS
## 8 TP53 NF1
##
## $fit$clones_expansions$CRUK0031
## # A tibble: 8 x 2
## from to
## <chr> <chr>
## 1 GL KEAP1
## 2 GL CDKN2A
## 3 GL PRF1
## 4 GL FGFR1
## 5 KEAP1 NF1
## 6 CDKN2A NF1
## 7 PRF1 NF1
## 8 FGFR1 NF1
##
## $fit$clones_expansions$CRUK0032
## # A tibble: 9 x 2
## from to
## <chr> <chr>
## 1 GL ATM
## 2 GL RAD21
## 3 GL U2AF1
## 4 GL RNF43
## 5 ATM CCND1
## 6 RAD21 CCND1
## 7 U2AF1 CCND1
## 8 RNF43 CCND1
## 9 CCND1 ARID1B
##
## $fit$clones_expansions$CRUK0033
## # A tibble: 2 x 2
## from to
## <chr> <chr>
## 1 GL KEAP1
## 2 GL CTNNB1
##
## $fit$clones_expansions$CRUK0034
## # A tibble: 5 x 2
## from to
## <chr> <chr>
## 1 GL KRAS
## 2 GL ATM
## 3 KRAS PLXNB2
## 4 ATM MGA
## 5 PLXNB2 MGA
##
## $fit$clones_expansions$CRUK0035
## # A tibble: 3 x 2
## from to
## <chr> <chr>
## 1 GL TP53
## 2 TP53 FAS
## 3 FAS FLT4
##
## $fit$clones_expansions$CRUK0036
## # A tibble: 7 x 2
## from to
## <chr> <chr>
## 1 GL ARHGAP35
## 2 GL KEAP1
## 3 GL PIK3CA
## 4 ARHGAP35 TERT
## 5 KEAP1 KRAS
## 6 PIK3CA TERT
## 7 TERT KRAS
##
## $fit$clones_expansions$CRUK0037
## # A tibble: 3 x 2
## from to
## <chr> <chr>
## 1 GL NCOA6
## 2 GL CREBBP
## 3 GL KRAS
##
## $fit$clones_expansions$CRUK0038
## # A tibble: 2 x 2
## from to
## <chr> <chr>
## 1 GL KRAS
## 2 KRAS KMT2D
##
## $fit$clones_expansions$CRUK0039
## # A tibble: 4 x 2
## from to
## <chr> <chr>
## 1 GL KRAS
## 2 GL CMTR2
## 3 GL NF1
## 4 GL PHOX2B
##
## $fit$clones_expansions$CRUK0040
## # A tibble: 4 x 2
## from to
## <chr> <chr>
## 1 GL KRAS
## 2 GL RAD21
## 3 GL GATA3
## 4 KRAS NCOR1
##
## $fit$clones_expansions$CRUK0041
## # A tibble: 3 x 2
## from to
## <chr> <chr>
## 1 GL BRAF
## 2 GL EGFR
## 3 BRAF TERT
##
## $fit$clones_expansions$CRUK0042
## # A tibble: 1 x 2
## from to
## <chr> <chr>
## 1 GL KRAS
##
## $fit$clones_expansions$CRUK0043
## # A tibble: 1 x 2
## from to
## <chr> <chr>
## 1 GL MET
##
## $fit$clones_expansions$CRUK0044
## # A tibble: 1 x 2
## from to
## <chr> <chr>
## 1 GL KRAS
##
## $fit$clones_expansions$CRUK0045
## # A tibble: 1 x 2
## from to
## <chr> <chr>
## 1 GL BAP1
##
## $fit$clones_expansions$CRUK0046
## # A tibble: 2 x 2
## from to
## <chr> <chr>
## 1 GL KEAP1
## 2 GL APC
##
## $fit$clones_expansions$CRUK0047
## # A tibble: 5 x 2
## from to
## <chr> <chr>
## 1 GL MYC
## 2 GL STK11
## 3 GL APC
## 4 MYC KRAS
## 5 STK11 KRAS
##
## $fit$clones_expansions$CRUK0048
## # A tibble: 8 x 2
## from to
## <chr> <chr>
## 1 GL EGFR
## 2 GL APC
## 3 GL PRDM1
## 4 GL BRAF
## 5 GL MYC
## 6 EGFR TP53
## 7 EGFR ARHGAP35
## 8 TP53 ARHGAP35
##
## $fit$clones_expansions$CRUK0049
## # A tibble: 8 x 2
## from to
## <chr> <chr>
## 1 GL EGFR
## 2 GL COL2A1
## 3 GL KRAS
## 4 GL TP53
## 5 EGFR TP53
## 6 EGFR RB1
## 7 KRAS TP53
## 8 TP53 KRAS
##
## $fit$clones_expansions$CRUK0050
## # A tibble: 4 x 2
## from to
## <chr> <chr>
## 1 GL MYC
## 2 GL STK11
## 3 MYC KRAS
## 4 STK11 KRAS
##
## $fit$clones_expansions$CRUK0051
## # A tibble: 10 x 2
## from to
## <chr> <chr>
## 1 GL EGFR
## 2 GL FBXW7
## 3 GL KRAS
## 4 GL TP53
## 5 EGFR TP53
## 6 KRAS TP53
## 7 TP53 KRAS
## 8 FBXW7 EP300
## 9 KRAS EP300
## 10 TP53 EP300
##
## $fit$clones_expansions$CRUK0052
## # A tibble: 19 x 2
## from to
## <chr> <chr>
## 1 GL KEAP1
## 2 GL NOTCH2
## 3 GL SGK223
## 4 GL KRAS
## 5 GL TP53
## 6 KEAP1 KRAS
## 7 KEAP1 NF1
## 8 KRAS MGA
## 9 KRAS TP53
## 10 KRAS KMT2D
## 11 MGA NF1
## 12 TP53 KRAS
## 13 TP53 NF1
## 14 KMT2D UBR5
## 15 NOTCH2 UBR5
## 16 NF1 UBR5
## 17 SGK223 UBR5
## 18 KRAS UBR5
## 19 TP53 UBR5
##
## $fit$clones_expansions$CRUK0054
## # A tibble: 1 x 2
## from to
## <chr> <chr>
## 1 GL EGFR
##
## $fit$clones_expansions$CRUK0055
## # A tibble: 4 x 2
## from to
## <chr> <chr>
## 1 GL FANCM
## 2 GL UBR5
## 3 FANCM FAT1
## 4 UBR5 FAT1
##
## $fit$clones_expansions$CRUK0056
## # A tibble: 4 x 2
## from to
## <chr> <chr>
## 1 GL RASA1
## 2 GL CREBBP
## 3 RASA1 TP53
## 4 CREBBP TP53
##
## $fit$clones_expansions$CRUK0057
## # A tibble: 5 x 2
## from to
## <chr> <chr>
## 1 GL TERT
## 2 GL SMARCA4
## 3 GL TSC2
## 4 TERT KRAS
## 5 TERT DNM2
##
## $fit$clones_expansions$CRUK0058
## # A tibble: 2 x 2
## from to
## <chr> <chr>
## 1 GL EGFR
## 2 EGFR TP53
##
## $fit$clones_expansions$CRUK0059
## # A tibble: 1 x 2
## from to
## <chr> <chr>
## 1 GL KRAS
##
## $fit$clones_expansions$CRUK0060
## # A tibble: 12 x 2
## from to
## <chr> <chr>
## 1 GL NCOA6
## 2 GL NF1
## 3 GL SERPINB13
## 4 GL ARID2
## 5 GL PHOX2B
## 6 GL COL2A1
## 7 GL RASA1
## 8 GL NOTCH2
## 9 GL KMT2C
## 10 NCOA6 COL5A2
## 11 NF1 FANCM
## 12 SERPINB13 COL5A2
##
## $fit$clones_expansions$CRUK0061
## # A tibble: 1 x 2
## from to
## <chr> <chr>
## 1 GL STK11
##
## $fit$clones_expansions$CRUK0062
## # A tibble: 13 x 2
## from to
## <chr> <chr>
## 1 GL TP53
## 2 GL PIK3CA
## 3 GL SOX2
## 4 GL CCND1
## 5 TP53 UBR5
## 6 PIK3CA UBR5
## 7 SOX2 UBR5
## 8 CCND1 UBR5
## 9 TP53 FAS
## 10 PIK3CA FAS
## 11 SOX2 FAS
## 12 CCND1 FAS
## 13 UBR5 PLXNB2
##
## $fit$clones_expansions$CRUK0063
## # A tibble: 16 x 2
## from to
## <chr> <chr>
## 1 GL CDKN2A
## 2 GL PIK3CA
## 3 GL SOX2
## 4 GL FBXW7
## 5 GL PRF1
## 6 CDKN2A TP53
## 7 PIK3CA TERT
## 8 SOX2 TERT
## 9 TP53 TERT
## 10 FBXW7 EP300
## 11 TERT EP300
## 12 PRF1 EP300
## 13 EP300 NF1
## 14 EP300 CYLD
## 15 NF1 FANCM
## 16 CYLD FANCM
##
## $fit$clones_expansions$CRUK0064
## # A tibble: 3 x 2
## from to
## <chr> <chr>
## 1 GL TP53
## 2 TP53 MLH1
## 3 TP53 FAT1
##
## $fit$clones_expansions$CRUK0065
## # A tibble: 11 x 2
## from to
## <chr> <chr>
## 1 GL PIK3CA
## 2 GL SOX2
## 3 GL TP53
## 4 PIK3CA NFE2L2
## 5 SOX2 NFE2L2
## 6 TP53 NFE2L2
## 7 NFE2L2 MLH1
## 8 NFE2L2 PTPRC
## 9 NFE2L2 UBR5
## 10 NFE2L2 NOTCH1
## 11 NFE2L2 NCOA6
##
## $fit$clones_expansions$CRUK0066
## # A tibble: 12 x 2
## from to
## <chr> <chr>
## 1 GL CDKN2A
## 2 GL WRN
## 3 GL PDGFRA
## 4 CDKN2A TP53
## 5 TP53 NOTCH1
## 6 TP53 TERT
## 7 TP53 NCOA6
## 8 WRN TP53
## 9 NOTCH1 COL5A2
## 10 PDGFRA COL5A2
## 11 TERT COL5A2
## 12 NCOA6 COL5A2
##
## $fit$clones_expansions$CRUK0067
## # A tibble: 8 x 2
## from to
## <chr> <chr>
## 1 GL CDKN2A
## 2 GL PIK3CA
## 3 GL SOX2
## 4 CDKN2A TP53
## 5 PIK3CA NOTCH1
## 6 SOX2 NOTCH1
## 7 TP53 NOTCH1
## 8 NOTCH1 NFE2L2
##
## $fit$clones_expansions$CRUK0068
## # A tibble: 16 x 2
## from to
## <chr> <chr>
## 1 GL TP53
## 2 GL PTEN
## 3 GL KMT2D
## 4 GL PIK3CA
## 5 GL SOX2
## 6 TP53 SETD2
## 7 PTEN SETD2
## 8 KMT2D SETD2
## 9 PIK3CA SETD2
## 10 SOX2 SETD2
## 11 TP53 TERT
## 12 PTEN TERT
## 13 KMT2D TERT
## 14 PIK3CA TERT
## 15 SOX2 TERT
## 16 SETD2 MGA
##
## $fit$clones_expansions$CRUK0069
## # A tibble: 7 x 2
## from to
## <chr> <chr>
## 1 GL TP53
## 2 GL PDGFRA
## 3 GL FGFR1
## 4 TP53 FAT1
## 5 FAT1 KRAS
## 6 PDGFRA KRAS
## 7 FGFR1 KRAS
##
## $fit$clones_expansions$CRUK0070
## # A tibble: 9 x 2
## from to
## <chr> <chr>
## 1 GL SOX2
## 2 GL TP53
## 3 SOX2 COL5A2
## 4 TP53 DNM2
## 5 TP53 COL5A2
## 6 DNM2 CBLB
## 7 COL5A2 CBLB
## 8 DNM2 NFE2L2
## 9 COL5A2 NFE2L2
##
## $fit$clones_expansions$CRUK0071
## # A tibble: 6 x 2
## from to
## <chr> <chr>
## 1 GL CMTR2
## 2 GL PIK3CA
## 3 GL SOX2
## 4 CMTR2 UBR5
## 5 PIK3CA UBR5
## 6 SOX2 UBR5
##
## $fit$clones_expansions$CRUK0072
## # A tibble: 8 x 2
## from to
## <chr> <chr>
## 1 GL EGFR
## 2 GL PIK3CA
## 3 GL SOX2
## 4 GL MYC
## 5 EGFR TP53
## 6 PIK3CA NFE2L2
## 7 SOX2 NFE2L2
## 8 TP53 NFE2L2
##
## $fit$clones_expansions$CRUK0073
## # A tibble: 15 x 2
## from to
## <chr> <chr>
## 1 GL CDKN2A
## 2 GL FAT1
## 3 GL FGFR1
## 4 GL DICER1
## 5 GL NOTCH2
## 6 GL MYC
## 7 CDKN2A NFE2L2
## 8 CDKN2A KMT2D
## 9 FAT1 NFE2L2
## 10 FGFR1 NFE2L2
## 11 DICER1 PLXNB2
## 12 NFE2L2 PLXNB2
## 13 KMT2D PLXNB2
## 14 NOTCH2 PLXNB2
## 15 MYC PLXNB2
##
## $fit$clones_expansions$CRUK0074
## # A tibble: 9 x 2
## from to
## <chr> <chr>
## 1 GL PIK3CA
## 2 GL SOX2
## 3 GL TP53
## 4 GL CCND1
## 5 PIK3CA NFE2L2
## 6 SOX2 NFE2L2
## 7 TP53 NFE2L2
## 8 NFE2L2 UBR5
## 9 CCND1 UBR5
##
## $fit$clones_expansions$CRUK0075
## # A tibble: 12 x 2
## from to
## <chr> <chr>
## 1 GL PIK3CA
## 2 GL RASA1
## 3 GL MGA
## 4 GL FGFR1
## 5 PIK3CA NOTCH1
## 6 RASA1 TP53
## 7 TP53 NOTCH1
## 8 TP53 FAT1
## 9 NOTCH1 NFE2L2
## 10 FAT1 NFE2L2
## 11 MGA NFE2L2
## 12 FGFR1 NFE2L2
##
## $fit$clones_expansions$CRUK0076
## # A tibble: 12 x 2
## from to
## <chr> <chr>
## 1 GL TP53
## 2 GL SERPINB13
## 3 GL PIK3CA
## 4 GL SOX2
## 5 GL FGFR1
## 6 TP53 ARID1B
## 7 SERPINB13 COL5A2
## 8 ARID1B COL5A2
## 9 PIK3CA COL5A2
## 10 SOX2 COL5A2
## 11 FGFR1 COL5A2
## 12 COL5A2 NCOR1
##
## $fit$clones_expansions$CRUK0077
## # A tibble: 3 x 2
## from to
## <chr> <chr>
## 1 GL TP53
## 2 GL KEAP1
## 3 TP53 LATS1
##
## $fit$clones_expansions$CRUK0078
## # A tibble: 5 x 2
## from to
## <chr> <chr>
## 1 GL FGFR1
## 2 GL PTEN
## 3 GL PIK3CA
## 4 GL SOX2
## 5 FGFR1 PLXNB2
##
## $fit$clones_expansions$CRUK0079
## # A tibble: 6 x 2
## from to
## <chr> <chr>
## 1 GL TP53
## 2 GL POLE
## 3 GL PIK3CA
## 4 GL SOX2
## 5 GL FGFR1
## 6 TP53 FAT1
##
## $fit$clones_expansions$CRUK0080
## # A tibble: 7 x 2
## from to
## <chr> <chr>
## 1 GL EGFR
## 2 GL WT1
## 3 GL CCND1
## 4 EGFR TP53
## 5 TP53 IKZF1
## 6 WT1 IKZF1
## 7 CCND1 IKZF1
##
## $fit$clones_expansions$CRUK0081
## # A tibble: 8 x 2
## from to
## <chr> <chr>
## 1 GL CDKN2A
## 2 CDKN2A TP53
## 3 TP53 NOTCH1
## 4 TP53 FAT1
## 5 TP53 FANCC
## 6 NOTCH1 CYLD
## 7 FAT1 CYLD
## 8 FANCC CYLD
##
## $fit$clones_expansions$CRUK0082
## # A tibble: 11 x 2
## from to
## <chr> <chr>
## 1 GL FGFR1
## 2 GL PIK3CA
## 3 GL SOX2
## 4 GL TP53
## 5 GL WT1
## 6 GL PTEN
## 7 GL KMT2D
## 8 FGFR1 COL5A2
## 9 PIK3CA COL5A2
## 10 SOX2 COL5A2
## 11 TP53 COL5A2
##
## $fit$clones_expansions$CRUK0083
## # A tibble: 7 x 2
## from to
## <chr> <chr>
## 1 GL RASA1
## 2 GL FBXW7
## 3 GL PIK3CA
## 4 GL SOX2
## 5 GL FGFR1
## 6 GL MYC
## 7 RASA1 TP53
##
## $fit$clones_expansions$CRUK0084
## # A tibble: 1 x 2
## from to
## <chr> <chr>
## 1 GL CREBBP
##
## $fit$clones_expansions$CRUK0085
## # A tibble: 4 x 2
## from to
## <chr> <chr>
## 1 GL CHEK2
## 2 GL CREBBP
## 3 GL LATS1
## 4 GL FANCM
##
## $fit$clones_expansions$CRUK0086
## # A tibble: 3 x 2
## from to
## <chr> <chr>
## 1 GL TP53
## 2 GL ARID2
## 3 TP53 FAT1
##
## $fit$clones_expansions$CRUK0087
## # A tibble: 5 x 2
## from to
## <chr> <chr>
## 1 GL PIK3CA
## 2 GL TP53
## 3 GL ASXL1
## 4 PIK3CA NFE2L2
## 5 TP53 NFE2L2
##
## $fit$clones_expansions$CRUK0088
## # A tibble: 2 x 2
## from to
## <chr> <chr>
## 1 GL CUX1
## 2 GL TP53
##
## $fit$clones_expansions$CRUK0089
## # A tibble: 3 x 2
## from to
## <chr> <chr>
## 1 GL PIK3CA
## 2 GL SMAD4
## 3 GL KEAP1
##
## $fit$clones_expansions$CRUK0090
## # A tibble: 5 x 2
## from to
## <chr> <chr>
## 1 GL CDKN2A
## 2 GL NCOA6
## 3 GL CUX1
## 4 GL COL2A1
## 5 GL NRAS
##
## $fit$clones_expansions$CRUK0091
## # A tibble: 3 x 2
## from to
## <chr> <chr>
## 1 GL CDKN2A
## 2 GL SMARCA4
## 3 CDKN2A TP53
##
## $fit$clones_expansions$CRUK0092
## # A tibble: 5 x 2
## from to
## <chr> <chr>
## 1 GL RASA1
## 2 GL PIK3CA
## 3 RASA1 TP53
## 4 TP53 SMAD4
## 5 TP53 CBLB
##
## $fit$clones_expansions$CRUK0093
## # A tibble: 8 x 2
## from to
## <chr> <chr>
## 1 GL CDKN2A
## 2 GL DICER1
## 3 GL COL2A1
## 4 GL GATA3
## 5 CDKN2A TP53
## 6 CDKN2A COL5A2
## 7 TP53 CIC
## 8 TP53 COL5A2
##
## $fit$clones_expansions$CRUK0094
## # A tibble: 2 x 2
## from to
## <chr> <chr>
## 1 GL SMARCA4
## 2 GL TERT
##
## $fit$clones_expansions$CRUK0095
## # A tibble: 3 x 2
## from to
## <chr> <chr>
## 1 GL RASA1
## 2 RASA1 TP53
## 3 TP53 NF1
##
## $fit$clones_expansions$CRUK0096
## # A tibble: 3 x 2
## from to
## <chr> <chr>
## 1 GL KRAS
## 2 GL SGK223
## 3 GL MAP3K1
##
## $fit$clones_expansions$CRUK0097
## # A tibble: 2 x 2
## from to
## <chr> <chr>
## 1 GL TP53
## 2 GL PTEN
##
## $fit$clones_expansions$CRUK0098
## # A tibble: 4 x 2
## from to
## <chr> <chr>
## 1 GL TP53
## 2 GL PTEN
## 3 TP53 UBR5
## 4 PTEN UBR5
##
## $fit$clones_expansions$CRUK0099
## # A tibble: 3 x 2
## from to
## <chr> <chr>
## 1 GL STK11
## 2 GL KEAP1
## 3 GL TP53
##
## $fit$clones_expansions$CRUK0100
## # A tibble: 7 x 2
## from to
## <chr> <chr>
## 1 GL CDKN2A
## 2 GL PHOX2B
## 3 GL STK11
## 4 GL SPEN
## 5 CDKN2A TP53
## 6 CDKN2A COL5A2
## 7 TP53 COL5A2
##
##
##
## $cluster
## $cluster$distances
## $cluster$distances$matrix
## CRUK0001 CRUK0002 CRUK0003 CRUK0004 CRUK0005 CRUK0006 CRUK0007
## CRUK0001 0 67 90 60 105 110 76
## CRUK0002 0 0 71 54 66 71 57
## CRUK0003 0 0 0 77 109 114 60
## CRUK0004 0 0 0 0 92 97 63
## CRUK0005 0 0 0 0 0 72 95
## CRUK0006 0 0 0 0 0 0 100
## CRUK0007 0 0 0 0 0 0 0
## CRUK0008 0 0 0 0 0 0 0
## CRUK0009 0 0 0 0 0 0 0
## CRUK0010 0 0 0 0 0 0 0
## CRUK0011 0 0 0 0 0 0 0
## CRUK0012 0 0 0 0 0 0 0
## CRUK0013 0 0 0 0 0 0 0
## CRUK0014 0 0 0 0 0 0 0
## CRUK0015 0 0 0 0 0 0 0
## CRUK0016 0 0 0 0 0 0 0
## CRUK0017 0 0 0 0 0 0 0
## CRUK0018 0 0 0 0 0 0 0
## CRUK0019 0 0 0 0 0 0 0
## CRUK0020 0 0 0 0 0 0 0
## CRUK0021 0 0 0 0 0 0 0
## CRUK0022 0 0 0 0 0 0 0
## CRUK0023 0 0 0 0 0 0 0
## CRUK0024 0 0 0 0 0 0 0
## CRUK0025 0 0 0 0 0 0 0
## CRUK0026 0 0 0 0 0 0 0
## CRUK0027 0 0 0 0 0 0 0
## CRUK0028 0 0 0 0 0 0 0
## CRUK0029 0 0 0 0 0 0 0
## CRUK0030 0 0 0 0 0 0 0
## CRUK0031 0 0 0 0 0 0 0
## CRUK0032 0 0 0 0 0 0 0
## CRUK0033 0 0 0 0 0 0 0
## CRUK0034 0 0 0 0 0 0 0
## CRUK0035 0 0 0 0 0 0 0
## CRUK0036 0 0 0 0 0 0 0
## CRUK0037 0 0 0 0 0 0 0
## CRUK0038 0 0 0 0 0 0 0
## CRUK0039 0 0 0 0 0 0 0
## CRUK0040 0 0 0 0 0 0 0
## CRUK0041 0 0 0 0 0 0 0
## CRUK0042 0 0 0 0 0 0 0
## CRUK0043 0 0 0 0 0 0 0
## CRUK0044 0 0 0 0 0 0 0
## CRUK0045 0 0 0 0 0 0 0
## CRUK0046 0 0 0 0 0 0 0
## CRUK0047 0 0 0 0 0 0 0
## CRUK0048 0 0 0 0 0 0 0
## CRUK0049 0 0 0 0 0 0 0
## CRUK0050 0 0 0 0 0 0 0
## CRUK0051 0 0 0 0 0 0 0
## CRUK0052 0 0 0 0 0 0 0
## CRUK0054 0 0 0 0 0 0 0
## CRUK0055 0 0 0 0 0 0 0
## CRUK0056 0 0 0 0 0 0 0
## CRUK0057 0 0 0 0 0 0 0
## CRUK0058 0 0 0 0 0 0 0
## CRUK0059 0 0 0 0 0 0 0
## CRUK0060 0 0 0 0 0 0 0
## CRUK0061 0 0 0 0 0 0 0
## CRUK0062 0 0 0 0 0 0 0
## CRUK0063 0 0 0 0 0 0 0
## CRUK0064 0 0 0 0 0 0 0
## CRUK0065 0 0 0 0 0 0 0
## CRUK0066 0 0 0 0 0 0 0
## CRUK0067 0 0 0 0 0 0 0
## CRUK0068 0 0 0 0 0 0 0
## CRUK0069 0 0 0 0 0 0 0
## CRUK0070 0 0 0 0 0 0 0
## CRUK0071 0 0 0 0 0 0 0
## CRUK0072 0 0 0 0 0 0 0
## CRUK0073 0 0 0 0 0 0 0
## CRUK0074 0 0 0 0 0 0 0
## CRUK0075 0 0 0 0 0 0 0
## CRUK0076 0 0 0 0 0 0 0
## CRUK0077 0 0 0 0 0 0 0
## CRUK0078 0 0 0 0 0 0 0
## CRUK0079 0 0 0 0 0 0 0
## CRUK0080 0 0 0 0 0 0 0
## CRUK0081 0 0 0 0 0 0 0
## CRUK0082 0 0 0 0 0 0 0
## CRUK0083 0 0 0 0 0 0 0
## CRUK0084 0 0 0 0 0 0 0
## CRUK0085 0 0 0 0 0 0 0
## CRUK0086 0 0 0 0 0 0 0
## CRUK0087 0 0 0 0 0 0 0
## CRUK0088 0 0 0 0 0 0 0
## CRUK0089 0 0 0 0 0 0 0
## CRUK0090 0 0 0 0 0 0 0
## CRUK0091 0 0 0 0 0 0 0
## CRUK0092 0 0 0 0 0 0 0
## CRUK0093 0 0 0 0 0 0 0
## CRUK0094 0 0 0 0 0 0 0
## CRUK0095 0 0 0 0 0 0 0
## CRUK0096 0 0 0 0 0 0 0
## CRUK0097 0 0 0 0 0 0 0
## CRUK0098 0 0 0 0 0 0 0
## CRUK0099 0 0 0 0 0 0 0
## CRUK0100 0 0 0 0 0 0 0
## CRUK0008 CRUK0009 CRUK0010 CRUK0011 CRUK0012 CRUK0013 CRUK0014
## CRUK0001 94 107 57 74 53 67 123
## CRUK0002 55 66 38 35 34 28 84
## CRUK0003 98 114 61 78 57 71 127
## CRUK0004 81 97 44 61 40 54 110
## CRUK0005 93 71 76 73 72 66 91
## CRUK0006 86 83 81 78 77 71 96
## CRUK0007 84 100 47 64 43 57 113
## CRUK0008 0 98 65 62 61 47 111
## CRUK0009 0 0 81 78 77 71 96
## CRUK0010 0 0 0 45 24 38 94
## CRUK0011 0 0 0 0 41 35 71
## CRUK0012 0 0 0 0 0 34 90
## CRUK0013 0 0 0 0 0 0 84
## CRUK0014 0 0 0 0 0 0 0
## CRUK0015 0 0 0 0 0 0 0
## CRUK0016 0 0 0 0 0 0 0
## CRUK0017 0 0 0 0 0 0 0
## CRUK0018 0 0 0 0 0 0 0
## CRUK0019 0 0 0 0 0 0 0
## CRUK0020 0 0 0 0 0 0 0
## CRUK0021 0 0 0 0 0 0 0
## CRUK0022 0 0 0 0 0 0 0
## CRUK0023 0 0 0 0 0 0 0
## CRUK0024 0 0 0 0 0 0 0
## CRUK0025 0 0 0 0 0 0 0
## CRUK0026 0 0 0 0 0 0 0
## CRUK0027 0 0 0 0 0 0 0
## CRUK0028 0 0 0 0 0 0 0
## CRUK0029 0 0 0 0 0 0 0
## CRUK0030 0 0 0 0 0 0 0
## CRUK0031 0 0 0 0 0 0 0
## CRUK0032 0 0 0 0 0 0 0
## CRUK0033 0 0 0 0 0 0 0
## CRUK0034 0 0 0 0 0 0 0
## CRUK0035 0 0 0 0 0 0 0
## CRUK0036 0 0 0 0 0 0 0
## CRUK0037 0 0 0 0 0 0 0
## CRUK0038 0 0 0 0 0 0 0
## CRUK0039 0 0 0 0 0 0 0
## CRUK0040 0 0 0 0 0 0 0
## CRUK0041 0 0 0 0 0 0 0
## CRUK0042 0 0 0 0 0 0 0
## CRUK0043 0 0 0 0 0 0 0
## CRUK0044 0 0 0 0 0 0 0
## CRUK0045 0 0 0 0 0 0 0
## CRUK0046 0 0 0 0 0 0 0
## CRUK0047 0 0 0 0 0 0 0
## CRUK0048 0 0 0 0 0 0 0
## CRUK0049 0 0 0 0 0 0 0
## CRUK0050 0 0 0 0 0 0 0
## CRUK0051 0 0 0 0 0 0 0
## CRUK0052 0 0 0 0 0 0 0
## CRUK0054 0 0 0 0 0 0 0
## CRUK0055 0 0 0 0 0 0 0
## CRUK0056 0 0 0 0 0 0 0
## CRUK0057 0 0 0 0 0 0 0
## CRUK0058 0 0 0 0 0 0 0
## CRUK0059 0 0 0 0 0 0 0
## CRUK0060 0 0 0 0 0 0 0
## CRUK0061 0 0 0 0 0 0 0
## CRUK0062 0 0 0 0 0 0 0
## CRUK0063 0 0 0 0 0 0 0
## CRUK0064 0 0 0 0 0 0 0
## CRUK0065 0 0 0 0 0 0 0
## CRUK0066 0 0 0 0 0 0 0
## CRUK0067 0 0 0 0 0 0 0
## CRUK0068 0 0 0 0 0 0 0
## CRUK0069 0 0 0 0 0 0 0
## CRUK0070 0 0 0 0 0 0 0
## CRUK0071 0 0 0 0 0 0 0
## CRUK0072 0 0 0 0 0 0 0
## CRUK0073 0 0 0 0 0 0 0
## CRUK0074 0 0 0 0 0 0 0
## CRUK0075 0 0 0 0 0 0 0
## CRUK0076 0 0 0 0 0 0 0
## CRUK0077 0 0 0 0 0 0 0
## CRUK0078 0 0 0 0 0 0 0
## CRUK0079 0 0 0 0 0 0 0
## CRUK0080 0 0 0 0 0 0 0
## CRUK0081 0 0 0 0 0 0 0
## CRUK0082 0 0 0 0 0 0 0
## CRUK0083 0 0 0 0 0 0 0
## CRUK0084 0 0 0 0 0 0 0
## CRUK0085 0 0 0 0 0 0 0
## CRUK0086 0 0 0 0 0 0 0
## CRUK0087 0 0 0 0 0 0 0
## CRUK0088 0 0 0 0 0 0 0
## CRUK0089 0 0 0 0 0 0 0
## CRUK0090 0 0 0 0 0 0 0
## CRUK0091 0 0 0 0 0 0 0
## CRUK0092 0 0 0 0 0 0 0
## CRUK0093 0 0 0 0 0 0 0
## CRUK0094 0 0 0 0 0 0 0
## CRUK0095 0 0 0 0 0 0 0
## CRUK0096 0 0 0 0 0 0 0
## CRUK0097 0 0 0 0 0 0 0
## CRUK0098 0 0 0 0 0 0 0
## CRUK0099 0 0 0 0 0 0 0
## CRUK0100 0 0 0 0 0 0 0
## CRUK0015 CRUK0016 CRUK0017 CRUK0018 CRUK0019 CRUK0020 CRUK0021
## CRUK0001 60 113 114 82 53 165 79
## CRUK0002 54 74 75 43 34 126 73
## CRUK0003 77 103 118 86 57 169 82
## CRUK0004 47 100 101 69 40 152 66
## CRUK0005 92 106 82 77 72 133 111
## CRUK0006 97 111 75 86 77 126 116
## CRUK0007 63 103 104 72 43 155 82
## CRUK0008 81 101 77 70 61 138 100
## CRUK0009 97 117 87 86 77 138 116
## CRUK0010 44 84 85 53 24 136 63
## CRUK0011 61 81 82 30 41 113 80
## CRUK0012 40 80 81 49 20 132 59
## CRUK0013 54 74 75 43 34 126 73
## CRUK0014 110 130 100 79 90 114 129
## CRUK0015 0 100 101 69 40 152 66
## CRUK0016 0 0 121 89 80 172 95
## CRUK0017 0 0 0 90 81 125 120
## CRUK0018 0 0 0 0 49 117 88
## CRUK0019 0 0 0 0 0 132 59
## CRUK0020 0 0 0 0 0 0 171
## CRUK0021 0 0 0 0 0 0 0
## CRUK0022 0 0 0 0 0 0 0
## CRUK0023 0 0 0 0 0 0 0
## CRUK0024 0 0 0 0 0 0 0
## CRUK0025 0 0 0 0 0 0 0
## CRUK0026 0 0 0 0 0 0 0
## CRUK0027 0 0 0 0 0 0 0
## CRUK0028 0 0 0 0 0 0 0
## CRUK0029 0 0 0 0 0 0 0
## CRUK0030 0 0 0 0 0 0 0
## CRUK0031 0 0 0 0 0 0 0
## CRUK0032 0 0 0 0 0 0 0
## CRUK0033 0 0 0 0 0 0 0
## CRUK0034 0 0 0 0 0 0 0
## CRUK0035 0 0 0 0 0 0 0
## CRUK0036 0 0 0 0 0 0 0
## CRUK0037 0 0 0 0 0 0 0
## CRUK0038 0 0 0 0 0 0 0
## CRUK0039 0 0 0 0 0 0 0
## CRUK0040 0 0 0 0 0 0 0
## CRUK0041 0 0 0 0 0 0 0
## CRUK0042 0 0 0 0 0 0 0
## CRUK0043 0 0 0 0 0 0 0
## CRUK0044 0 0 0 0 0 0 0
## CRUK0045 0 0 0 0 0 0 0
## CRUK0046 0 0 0 0 0 0 0
## CRUK0047 0 0 0 0 0 0 0
## CRUK0048 0 0 0 0 0 0 0
## CRUK0049 0 0 0 0 0 0 0
## CRUK0050 0 0 0 0 0 0 0
## CRUK0051 0 0 0 0 0 0 0
## CRUK0052 0 0 0 0 0 0 0
## CRUK0054 0 0 0 0 0 0 0
## CRUK0055 0 0 0 0 0 0 0
## CRUK0056 0 0 0 0 0 0 0
## CRUK0057 0 0 0 0 0 0 0
## CRUK0058 0 0 0 0 0 0 0
## CRUK0059 0 0 0 0 0 0 0
## CRUK0060 0 0 0 0 0 0 0
## CRUK0061 0 0 0 0 0 0 0
## CRUK0062 0 0 0 0 0 0 0
## CRUK0063 0 0 0 0 0 0 0
## CRUK0064 0 0 0 0 0 0 0
## CRUK0065 0 0 0 0 0 0 0
## CRUK0066 0 0 0 0 0 0 0
## CRUK0067 0 0 0 0 0 0 0
## CRUK0068 0 0 0 0 0 0 0
## CRUK0069 0 0 0 0 0 0 0
## CRUK0070 0 0 0 0 0 0 0
## CRUK0071 0 0 0 0 0 0 0
## CRUK0072 0 0 0 0 0 0 0
## CRUK0073 0 0 0 0 0 0 0
## CRUK0074 0 0 0 0 0 0 0
## CRUK0075 0 0 0 0 0 0 0
## CRUK0076 0 0 0 0 0 0 0
## CRUK0077 0 0 0 0 0 0 0
## CRUK0078 0 0 0 0 0 0 0
## CRUK0079 0 0 0 0 0 0 0
## CRUK0080 0 0 0 0 0 0 0
## CRUK0081 0 0 0 0 0 0 0
## CRUK0082 0 0 0 0 0 0 0
## CRUK0083 0 0 0 0 0 0 0
## CRUK0084 0 0 0 0 0 0 0
## CRUK0085 0 0 0 0 0 0 0
## CRUK0086 0 0 0 0 0 0 0
## CRUK0087 0 0 0 0 0 0 0
## CRUK0088 0 0 0 0 0 0 0
## CRUK0089 0 0 0 0 0 0 0
## CRUK0090 0 0 0 0 0 0 0
## CRUK0091 0 0 0 0 0 0 0
## CRUK0092 0 0 0 0 0 0 0
## CRUK0093 0 0 0 0 0 0 0
## CRUK0094 0 0 0 0 0 0 0
## CRUK0095 0 0 0 0 0 0 0
## CRUK0096 0 0 0 0 0 0 0
## CRUK0097 0 0 0 0 0 0 0
## CRUK0098 0 0 0 0 0 0 0
## CRUK0099 0 0 0 0 0 0 0
## CRUK0100 0 0 0 0 0 0 0
## CRUK0022 CRUK0023 CRUK0024 CRUK0025 CRUK0026 CRUK0027 CRUK0028
## CRUK0001 55 115 68 125 59 125 57
## CRUK0002 49 82 42 86 53 86 38
## CRUK0003 72 111 85 129 76 129 61
## CRUK0004 42 108 55 112 46 112 44
## CRUK0005 87 120 80 93 91 93 76
## CRUK0006 92 125 85 98 96 96 81
## CRUK0007 58 111 71 115 62 115 47
## CRUK0008 76 109 61 113 80 113 65
## CRUK0009 92 125 85 98 96 98 81
## CRUK0010 39 92 52 96 43 96 28
## CRUK0011 56 69 49 73 60 73 45
## CRUK0012 35 88 48 92 39 92 24
## CRUK0013 49 82 32 86 53 86 38
## CRUK0014 105 109 98 74 109 74 94
## CRUK0015 42 108 55 112 43 112 44
## CRUK0016 95 104 88 132 99 132 84
## CRUK0017 96 129 89 102 100 102 85
## CRUK0018 64 77 57 77 68 81 53
## CRUK0019 35 88 48 92 39 92 24
## CRUK0020 147 151 140 112 151 116 136
## CRUK0021 61 103 74 131 65 131 63
## CRUK0022 0 103 50 107 41 107 39
## CRUK0023 0 0 96 111 107 111 92
## CRUK0024 0 0 0 100 54 100 52
## CRUK0025 0 0 0 0 111 76 96
## CRUK0026 0 0 0 0 0 111 43
## CRUK0027 0 0 0 0 0 0 96
## CRUK0028 0 0 0 0 0 0 0
## CRUK0029 0 0 0 0 0 0 0
## CRUK0030 0 0 0 0 0 0 0
## CRUK0031 0 0 0 0 0 0 0
## CRUK0032 0 0 0 0 0 0 0
## CRUK0033 0 0 0 0 0 0 0
## CRUK0034 0 0 0 0 0 0 0
## CRUK0035 0 0 0 0 0 0 0
## CRUK0036 0 0 0 0 0 0 0
## CRUK0037 0 0 0 0 0 0 0
## CRUK0038 0 0 0 0 0 0 0
## CRUK0039 0 0 0 0 0 0 0
## CRUK0040 0 0 0 0 0 0 0
## CRUK0041 0 0 0 0 0 0 0
## CRUK0042 0 0 0 0 0 0 0
## CRUK0043 0 0 0 0 0 0 0
## CRUK0044 0 0 0 0 0 0 0
## CRUK0045 0 0 0 0 0 0 0
## CRUK0046 0 0 0 0 0 0 0
## CRUK0047 0 0 0 0 0 0 0
## CRUK0048 0 0 0 0 0 0 0
## CRUK0049 0 0 0 0 0 0 0
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##
## $cluster$distances$dist_obj
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## CRUK0022 CRUK0023 CRUK0024 CRUK0025 CRUK0026 CRUK0027 CRUK0028
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## CRUK0059 23 20 22 36 45 75 109
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## CRUK0070 78 135 138 77 62 73 70
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## CRUK0089 54 142 133 53 38 49 46
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## CRUK0091 48 136 139 47 32 43 37
## CRUK0092 56 144 147 55 40 40 48
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## CRUK0098 61 118 118 60 45 56 53
## CRUK0099 64 129 120 71 56 67 64
## CRUK0100 56 152 155 63 48 59 56
## CRUK0058 CRUK0059 CRUK0060 CRUK0061 CRUK0062 CRUK0063 CRUK0064
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## CRUK0015 40 60 75 48 124 127 79
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## CRUK0043 36 23 38 11 87 90 42
## CRUK0044 53 20 55 28 104 107 59
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## CRUK0049 109 109 139 117 162 196 117
## CRUK0050 54 41 56 21 105 108 60
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## CRUK0071 76 63 78 51 89 96 82
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## CRUK0073 82 69 81 57 133 122 88
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## CRUK0075 97 84 93 72 128 131 96
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## CRUK0081 73 60 75 48 124 103 72
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## CRUK0088 66 53 68 41 86 120 41
## CRUK0089 66 53 68 41 97 100 72
## CRUK0090 58 45 52 33 109 98 64
## CRUK0091 60 47 62 35 111 90 66
## CRUK0092 68 55 64 43 99 102 74
## CRUK0093 74 61 71 49 125 104 80
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## CRUK0095 48 35 44 23 99 102 54
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## CRUK0097 69 56 71 44 89 123 44
## CRUK0098 73 60 75 48 90 127 48
## CRUK0099 84 71 86 51 104 138 59
## CRUK0100 76 63 75 43 127 106 82
## CRUK0065 CRUK0066 CRUK0067 CRUK0068 CRUK0069 CRUK0070 CRUK0071
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## CRUK0004 123 84 103 131 92 97 83
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## CRUK0014 122 119 138 130 91 96 113
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## CRUK0039 112 78 97 120 81 86 68
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## CRUK0051 161 158 177 169 130 135 152
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## CRUK0058 116 82 101 124 85 90 76
## CRUK0059 103 69 88 111 72 77 63
## CRUK0060 118 82 103 126 87 92 78
## CRUK0061 91 57 76 99 60 65 51
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## CRUK0064 91 88 107 99 53 65 82
## CRUK0065 132 117 109 104 95 92
## CRUK0066 132 88 134 99 106 92
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## CRUK0068 109 134 125 112 103 100
## CRUK0069 104 99 120 112 78 95
## CRUK0070 95 106 111 103 78 86
## CRUK0071 92 92 77 100 95 86
## CRUK0072 124 136 121 144 139 130 96
## CRUK0073 132 84 103 140 92 106 92
## CRUK0074 89 134 119 111 106 97 94
## CRUK0075 127 108 103 135 100 121 87
## CRUK0076 108 139 124 116 102 99 99
## CRUK0077 96 93 112 104 65 70 87
## CRUK0078 98 98 83 101 92 92 58
## CRUK0079 101 132 117 109 88 95 92
## CRUK0080 125 91 110 133 94 99 85
## CRUK0081 123 60 79 131 85 97 83
## CRUK0082 112 143 128 113 106 99 103
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## CRUK0086 92 89 108 100 54 66 83
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## CRUK0088 85 82 101 93 54 59 76
## CRUK0089 96 82 81 104 85 90 56
## CRUK0090 108 60 79 116 77 82 68
## CRUK0091 110 52 71 118 79 84 70
## CRUK0092 98 84 83 106 87 92 58
## CRUK0093 124 66 85 132 93 94 84
## CRUK0094 89 55 74 97 58 63 49
## CRUK0095 98 64 83 106 67 72 58
## CRUK0096 107 73 92 115 76 81 67
## CRUK0097 88 85 104 91 57 62 79
## CRUK0098 92 89 108 95 61 66 83
## CRUK0099 103 100 119 111 72 77 94
## CRUK0100 126 68 87 134 95 96 86
## CRUK0072 CRUK0073 CRUK0074 CRUK0075 CRUK0076 CRUK0077 CRUK0078
## CRUK0001 107 102 138 114 143 97 102
## CRUK0002 101 63 99 78 104 58 63
## CRUK0003 104 92 122 101 127 101 86
## CRUK0004 94 89 125 99 130 84 89
## CRUK0005 139 101 106 116 111 65 101
## CRUK0006 144 106 111 121 116 58 106
## CRUK0007 90 92 108 87 113 87 72
## CRUK0008 120 82 126 105 131 73 90
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## CRUK0010 91 73 109 88 114 68 73
## CRUK0011 108 70 106 85 111 65 70
## CRUK0012 87 69 105 84 110 64 69
## CRUK0013 101 63 99 78 104 58 63
## CRUK0014 157 119 124 134 129 83 119
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## CRUK0018 116 78 114 93 119 73 78
## CRUK0019 87 69 105 84 110 64 69
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## CRUK0027 159 121 126 136 131 85 121
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## CRUK0034 113 75 111 90 116 70 75
## CRUK0035 121 83 88 98 93 47 83
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## CRUK0039 116 78 114 93 119 73 78
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## CRUK0043 90 52 88 67 93 47 52
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## CRUK0051 163 158 163 173 168 122 158
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## CRUK0057 100 62 98 77 103 57 62
## CRUK0058 87 82 118 97 123 77 82
## CRUK0059 107 69 105 84 110 64 69
## CRUK0060 122 81 120 93 120 79 84
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## CRUK0062 137 133 98 128 109 97 99
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## CRUK0064 126 88 93 96 98 52 88
## CRUK0065 124 132 89 127 108 96 98
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## CRUK0070 130 106 97 121 99 70 92
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## CRUK0072 128 126 131 143 131 102
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## CRUK0075 131 100 129 125 108 84
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## CRUK0080 96 91 123 106 132 86 91
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## CRUK0089 100 82 98 77 103 65 62
## CRUK0090 112 60 110 89 115 69 74
## CRUK0091 114 62 112 91 117 71 76
## CRUK0092 102 84 100 68 105 79 64
## CRUK0093 128 74 126 105 131 85 90
## CRUK0094 93 55 91 70 96 50 55
## CRUK0095 102 64 100 68 105 59 64
## CRUK0096 111 73 109 88 114 68 73
## CRUK0097 123 85 90 100 95 49 80
## CRUK0098 127 89 94 104 99 53 84
## CRUK0099 138 100 105 115 110 52 100
## CRUK0100 130 78 128 107 133 87 92
## CRUK0079 CRUK0080 CRUK0081 CRUK0082 CRUK0083 CRUK0084 CRUK0085
## CRUK0001 136 62 93 147 119 57 62
## CRUK0002 97 56 54 108 80 18 23
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## CRUK0004 123 49 75 134 106 44 49
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## CRUK0012 103 42 60 114 86 24 29
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## CRUK0014 122 112 110 133 136 74 79
## CRUK0015 123 49 80 134 106 44 49
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## CRUK0017 113 103 101 124 119 65 70
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## CRUK0019 103 42 60 114 86 24 29
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## CRUK0022 118 44 75 129 101 39 44
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## CRUK0025 124 114 112 135 138 76 81
## CRUK0026 122 48 79 133 105 43 48
## CRUK0027 124 114 112 135 138 76 81
## CRUK0028 107 46 64 118 90 28 33
## CRUK0029 91 77 79 102 105 43 48
## CRUK0030 133 123 121 144 143 85 90
## CRUK0031 117 85 69 128 100 47 52
## CRUK0032 96 55 53 107 79 17 22
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## CRUK0034 109 68 66 120 92 30 35
## CRUK0035 86 76 74 97 100 38 43
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## CRUK0038 106 65 63 117 89 27 32
## CRUK0039 112 71 69 123 95 33 38
## CRUK0040 109 68 66 120 92 30 35
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## CRUK0044 103 62 60 114 86 24 29
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## CRUK0049 161 118 149 172 175 113 118
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## CRUK0051 161 118 149 172 171 113 118
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## CRUK0054 103 42 60 114 86 24 29
## CRUK0055 88 47 45 99 71 9 12
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## CRUK0058 116 42 73 127 99 37 42
## CRUK0059 103 62 60 114 86 24 29
## CRUK0060 118 77 75 129 95 39 44
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## CRUK0062 102 122 124 113 116 88 93
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## CRUK0064 84 81 72 102 105 43 48
## CRUK0065 101 125 123 112 115 87 92
## CRUK0066 132 91 60 143 115 53 58
## CRUK0067 117 110 79 128 100 72 77
## CRUK0068 109 133 131 113 123 95 100
## CRUK0069 88 94 85 106 109 56 61
## CRUK0070 95 99 97 99 109 61 66
## CRUK0071 92 85 83 103 75 47 52
## CRUK0072 136 96 127 147 111 91 96
## CRUK0073 123 91 75 134 98 53 58
## CRUK0074 103 123 125 114 117 89 94
## CRUK0075 111 106 92 129 90 68 73
## CRUK0076 99 132 130 103 113 94 99
## CRUK0077 96 86 84 107 110 48 53
## CRUK0078 89 91 89 95 72 53 58
## CRUK0079 125 116 103 106 87 92
## CRUK0080 125 82 134 108 46 51
## CRUK0081 116 82 134 106 44 49
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## CRUK0084 87 46 44 98 70 9
## CRUK0085 92 51 49 103 75 9
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## CRUK0087 93 103 101 104 107 65 70
## CRUK0088 85 75 73 96 99 37 42
## CRUK0089 96 75 73 107 79 37 42
## CRUK0090 108 67 51 119 91 29 34
## CRUK0091 110 69 43 121 93 31 36
## CRUK0092 98 77 75 109 70 39 44
## CRUK0093 124 83 57 131 107 45 50
## CRUK0094 89 48 46 100 72 10 15
## CRUK0095 98 57 55 109 70 19 24
## CRUK0096 107 66 64 118 90 28 33
## CRUK0097 88 78 76 94 102 40 45
## CRUK0098 92 82 80 98 106 44 49
## CRUK0099 103 93 91 114 117 55 60
## CRUK0100 126 85 59 133 109 47 52
## CRUK0086 CRUK0087 CRUK0088 CRUK0089 CRUK0090 CRUK0091 CRUK0092
## CRUK0001 93 114 86 86 78 80 88
## CRUK0002 54 75 47 47 39 41 49
## CRUK0003 97 98 90 70 68 70 72
## CRUK0004 80 101 73 73 65 67 73
## CRUK0005 61 82 54 85 77 79 87
## CRUK0006 66 87 59 78 82 84 92
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## CRUK0008 81 102 74 62 66 68 76
## CRUK0009 66 82 59 90 82 84 92
## CRUK0010 64 85 57 57 49 51 59
## CRUK0011 61 82 54 54 46 48 56
## CRUK0012 60 81 53 53 45 47 55
## CRUK0013 54 75 47 47 39 41 49
## CRUK0014 79 100 72 103 95 97 105
## CRUK0015 80 101 73 73 65 67 75
## CRUK0016 93 121 93 93 71 63 93
## CRUK0017 70 91 63 82 86 88 96
## CRUK0018 69 90 62 62 54 56 64
## CRUK0019 60 81 53 53 45 47 55
## CRUK0020 121 142 114 133 132 139 147
## CRUK0021 99 120 92 92 70 62 94
## CRUK0022 75 96 68 68 60 62 70
## CRUK0023 108 129 101 101 79 71 103
## CRUK0024 68 89 61 61 53 55 63
## CRUK0025 81 102 74 105 97 99 107
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## CRUK0027 81 102 74 105 97 99 107
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## CRUK0029 48 69 41 72 64 66 74
## CRUK0030 90 111 83 114 106 108 116
## CRUK0031 83 104 76 64 54 56 78
## CRUK0032 53 74 46 46 38 40 48
## CRUK0033 53 74 46 34 38 40 48
## CRUK0034 66 87 59 59 51 53 61
## CRUK0035 43 64 36 67 59 61 69
## CRUK0036 84 85 77 45 69 71 59
## CRUK0037 67 88 60 60 49 54 62
## CRUK0038 63 84 56 56 48 50 58
## CRUK0039 69 90 62 62 54 56 64
## CRUK0040 66 87 59 59 51 53 61
## CRUK0041 67 88 60 60 52 54 62
## CRUK0042 60 81 53 53 45 47 55
## CRUK0043 43 64 36 36 28 30 38
## CRUK0044 60 81 53 53 45 47 55
## CRUK0045 42 63 35 35 27 29 37
## CRUK0046 56 77 49 37 41 43 51
## CRUK0047 65 86 58 58 50 52 60
## CRUK0048 95 116 88 88 80 82 90
## CRUK0049 118 139 111 142 129 136 144
## CRUK0050 61 82 54 54 46 48 56
## CRUK0051 118 139 111 142 134 136 144
## CRUK0052 121 142 114 133 137 139 147
## CRUK0054 60 81 53 53 45 47 55
## CRUK0055 45 66 38 38 30 32 40
## CRUK0056 56 77 49 49 41 43 40
## CRUK0057 53 74 46 46 38 37 48
## CRUK0058 73 94 66 66 58 60 68
## CRUK0059 60 81 53 53 45 47 55
## CRUK0060 73 96 68 68 52 62 64
## CRUK0061 48 69 41 41 33 35 43
## CRUK0062 93 94 86 97 109 111 99
## CRUK0063 127 128 120 100 98 90 102
## CRUK0064 41 69 41 72 64 66 74
## CRUK0065 92 84 85 96 108 110 98
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## CRUK0067 108 109 101 81 79 71 83
## CRUK0068 100 101 93 104 116 118 106
## CRUK0069 54 82 54 85 77 79 87
## CRUK0070 66 87 59 90 82 84 92
## CRUK0071 83 84 76 56 68 70 58
## CRUK0072 127 119 120 100 112 114 102
## CRUK0073 89 110 82 82 60 62 84
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## CRUK0075 97 105 97 77 89 91 68
## CRUK0076 99 100 92 103 115 117 105
## CRUK0077 53 74 46 65 69 71 79
## CRUK0078 89 90 82 62 74 76 64
## CRUK0079 85 93 85 96 108 110 98
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## CRUK0081 73 101 73 73 51 43 75
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## CRUK0089 73 74 66 58 60 48
## CRUK0090 65 86 56 58 38 60
## CRUK0091 67 88 60 60 38 62
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## CRUK0097 45 66 38 69 61 63 71
## CRUK0098 49 70 42 73 65 67 75
## CRUK0099 60 81 53 72 76 78 86
## CRUK0100 83 104 76 76 54 46 78
## CRUK0093 CRUK0094 CRUK0095 CRUK0096 CRUK0097 CRUK0098 CRUK0099
## CRUK0001 94 59 64 77 89 93 104
## CRUK0002 55 20 29 38 50 54 65
## CRUK0003 84 63 72 81 93 97 108
## CRUK0004 81 46 55 64 76 80 91
## CRUK0005 93 58 67 76 57 61 72
## CRUK0006 98 63 72 81 62 66 65
## CRUK0007 84 49 58 64 79 83 94
## CRUK0008 82 47 56 65 77 81 72
## CRUK0009 98 63 72 81 62 66 77
## CRUK0010 65 27 39 48 60 64 75
## CRUK0011 62 27 36 25 57 61 72
## CRUK0012 61 26 35 44 56 60 71
## CRUK0013 55 20 29 38 50 54 57
## CRUK0014 111 76 85 74 75 79 90
## CRUK0015 81 46 55 64 76 80 91
## CRUK0016 77 66 75 84 96 100 111
## CRUK0017 102 67 76 85 66 70 69
## CRUK0018 70 35 44 33 65 69 80
## CRUK0019 61 26 35 44 56 60 71
## CRUK0020 148 118 127 116 117 121 120
## CRUK0021 76 65 74 83 95 99 110
## CRUK0022 74 41 50 59 71 75 86
## CRUK0023 85 74 83 72 104 108 119
## CRUK0024 69 34 43 52 64 68 71
## CRUK0025 113 78 87 76 77 81 92
## CRUK0026 80 45 54 63 75 79 90
## CRUK0027 113 78 87 76 77 81 92
## CRUK0028 65 30 39 48 60 64 75
## CRUK0029 80 45 54 63 44 48 59
## CRUK0030 122 87 92 85 86 90 101
## CRUK0031 70 49 58 67 79 83 82
## CRUK0032 54 19 28 37 49 53 64
## CRUK0033 54 19 28 37 49 53 52
## CRUK0034 67 32 41 30 62 66 77
## CRUK0035 75 40 49 58 39 43 54
## CRUK0036 85 50 59 68 80 84 83
## CRUK0037 68 33 42 31 63 67 78
## CRUK0038 64 29 38 27 59 63 74
## CRUK0039 70 35 44 33 65 69 80
## CRUK0040 65 32 41 30 62 66 77
## CRUK0041 68 33 42 51 63 67 78
## CRUK0042 61 26 35 24 56 60 71
## CRUK0043 44 9 18 27 39 43 54
## CRUK0044 61 26 35 24 56 60 71
## CRUK0045 43 8 17 26 38 42 53
## CRUK0046 57 22 31 40 52 56 55
## CRUK0047 66 31 40 49 61 65 68
## CRUK0048 96 61 70 79 91 95 106
## CRUK0049 145 115 124 113 114 118 129
## CRUK0050 62 27 36 45 57 61 64
## CRUK0051 150 115 124 113 114 118 129
## CRUK0052 153 118 123 113 117 118 120
## CRUK0054 61 26 35 44 56 60 71
## CRUK0055 46 11 20 29 41 45 56
## CRUK0056 57 22 20 40 52 56 67
## CRUK0057 54 13 28 37 49 53 64
## CRUK0058 74 39 48 57 69 73 84
## CRUK0059 61 26 35 24 56 60 71
## CRUK0060 71 41 44 59 71 75 86
## CRUK0061 49 14 23 32 44 48 51
## CRUK0062 125 90 99 108 89 90 104
## CRUK0063 104 93 102 111 123 127 138
## CRUK0064 80 45 54 63 44 48 59
## CRUK0065 124 89 98 107 88 92 103
## CRUK0066 66 55 64 73 85 89 100
## CRUK0067 85 74 83 92 104 108 119
## CRUK0068 132 97 106 115 91 95 111
## CRUK0069 93 58 67 76 57 61 72
## CRUK0070 94 63 72 81 62 66 77
## CRUK0071 84 49 58 67 79 83 94
## CRUK0072 128 93 102 111 123 127 138
## CRUK0073 74 55 64 73 85 89 100
## CRUK0074 126 91 100 109 90 94 105
## CRUK0075 105 70 68 88 100 104 115
## CRUK0076 131 96 105 114 95 99 110
## CRUK0077 85 50 59 68 49 53 52
## CRUK0078 90 55 64 73 80 84 100
## CRUK0079 124 89 98 107 88 92 103
## CRUK0080 83 48 57 66 78 82 93
## CRUK0081 57 46 55 64 76 80 91
## CRUK0082 131 100 109 118 94 98 114
## CRUK0083 107 72 70 90 102 106 117
## CRUK0084 45 10 19 28 40 44 55
## CRUK0085 50 15 24 33 45 49 60
## CRUK0086 81 46 55 64 45 49 60
## CRUK0087 102 67 76 85 66 70 81
## CRUK0088 74 39 48 57 38 42 53
## CRUK0089 74 39 48 57 69 73 72
## CRUK0090 47 31 40 49 61 65 76
## CRUK0091 44 30 42 51 63 67 78
## CRUK0092 76 41 39 59 71 75 86
## CRUK0093 47 56 65 77 81 92
## CRUK0094 47 21 30 42 46 57
## CRUK0095 56 21 39 51 55 66
## CRUK0096 65 30 39 60 64 75
## CRUK0097 77 42 51 60 40 56
## CRUK0098 81 46 55 64 40 60
## CRUK0099 92 57 66 75 56 60
## CRUK0100 54 49 58 67 79 83 86
## CRUK0100
## CRUK0001 96
## CRUK0002 57
## CRUK0003 86
## CRUK0004 83
## CRUK0005 95
## CRUK0006 100
## CRUK0007 86
## CRUK0008 76
## CRUK0009 100
## CRUK0010 67
## CRUK0011 64
## CRUK0012 63
## CRUK0013 49
## CRUK0014 113
## CRUK0015 83
## CRUK0016 77
## CRUK0017 104
## CRUK0018 72
## CRUK0019 63
## CRUK0020 155
## CRUK0021 78
## CRUK0022 78
## CRUK0023 87
## CRUK0024 63
## CRUK0025 115
## CRUK0026 82
## CRUK0027 115
## CRUK0028 67
## CRUK0029 82
## CRUK0030 124
## CRUK0031 72
## CRUK0032 56
## CRUK0033 56
## CRUK0034 69
## CRUK0035 77
## CRUK0036 87
## CRUK0037 70
## CRUK0038 66
## CRUK0039 69
## CRUK0040 69
## CRUK0041 70
## CRUK0042 63
## CRUK0043 46
## CRUK0044 63
## CRUK0045 45
## CRUK0046 59
## CRUK0047 60
## CRUK0048 98
## CRUK0049 152
## CRUK0050 56
## CRUK0051 152
## CRUK0052 155
## CRUK0054 63
## CRUK0055 48
## CRUK0056 59
## CRUK0057 56
## CRUK0058 76
## CRUK0059 63
## CRUK0060 75
## CRUK0061 43
## CRUK0062 127
## CRUK0063 106
## CRUK0064 82
## CRUK0065 126
## CRUK0066 68
## CRUK0067 87
## CRUK0068 134
## CRUK0069 95
## CRUK0070 96
## CRUK0071 86
## CRUK0072 130
## CRUK0073 78
## CRUK0074 128
## CRUK0075 107
## CRUK0076 133
## CRUK0077 87
## CRUK0078 92
## CRUK0079 126
## CRUK0080 85
## CRUK0081 59
## CRUK0082 133
## CRUK0083 109
## CRUK0084 47
## CRUK0085 52
## CRUK0086 83
## CRUK0087 104
## CRUK0088 76
## CRUK0089 76
## CRUK0090 54
## CRUK0091 46
## CRUK0092 78
## CRUK0093 54
## CRUK0094 49
## CRUK0095 58
## CRUK0096 67
## CRUK0097 79
## CRUK0098 83
## CRUK0099 86
## CRUK0100
##
##
## $cluster$parameters
## $cluster$parameters$hc.method
## [1] "ward"
##
## $cluster$parameters$split.method
## [1] "cutreeHybrid"
##
## $cluster$parameters$min.group.size
## [1] 2
##
##
## $cluster$fits
## $cluster$fits$hc
## Call: cluster::agnes(x = cluster$distances$dist_obj, method = hc.method)
## Agglomerative coefficient: 0.8491595
## Order of objects:
## [1] CRUK0001 CRUK0004 CRUK0015 CRUK0022 CRUK0058 CRUK0026 CRUK0080
## [8] CRUK0048 CRUK0021 CRUK0003 CRUK0007 CRUK0010 CRUK0012 CRUK0019
## [15] CRUK0054 CRUK0028 CRUK0041 CRUK0072 CRUK0002 CRUK0032 CRUK0043
## [22] CRUK0045 CRUK0084 CRUK0055 CRUK0094 CRUK0085 CRUK0057 CRUK0056
## [29] CRUK0095 CRUK0033 CRUK0046 CRUK0013 CRUK0061 CRUK0050 CRUK0047
## [36] CRUK0024 CRUK0060 CRUK0008 CRUK0031 CRUK0073 CRUK0016 CRUK0066
## [43] CRUK0081 CRUK0090 CRUK0091 CRUK0093 CRUK0100 CRUK0011 CRUK0042
## [50] CRUK0044 CRUK0059 CRUK0038 CRUK0096 CRUK0040 CRUK0034 CRUK0037
## [57] CRUK0018 CRUK0039 CRUK0023 CRUK0036 CRUK0089 CRUK0092 CRUK0071
## [64] CRUK0078 CRUK0083 CRUK0075 CRUK0063 CRUK0067 CRUK0005 CRUK0029
## [71] CRUK0035 CRUK0088 CRUK0097 CRUK0098 CRUK0064 CRUK0086 CRUK0069
## [78] CRUK0009 CRUK0070 CRUK0006 CRUK0077 CRUK0099 CRUK0017 CRUK0062
## [85] CRUK0065 CRUK0087 CRUK0074 CRUK0068 CRUK0076 CRUK0079 CRUK0082
## [92] CRUK0014 CRUK0027 CRUK0025 CRUK0030 CRUK0052 CRUK0020 CRUK0049
## [99] CRUK0051
## Height (summary):
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 5.00 31.95 56.07 68.11 87.69 352.24
##
## Available components:
## [1] "order" "height" "ac" "merge" "diss" "call"
## [7] "method" "order.lab"
##
## $cluster$fits$dendrogram
## 'dendrogram' with 2 branches and 99 members total, at height 352.2393
##
## $cluster$fits$K
## [1] 11
##
## $cluster$fits$labels
## CRUK0001 CRUK0004 CRUK0015 CRUK0022 CRUK0058 CRUK0026 CRUK0080 CRUK0048
## "C2" "C2" "C2" "C2" "C2" "C2" "C2" "C2"
## CRUK0021 CRUK0003 CRUK0007 CRUK0010 CRUK0012 CRUK0019 CRUK0054 CRUK0028
## "C2" "C2" "C2" "C2" "C2" "C2" "C2" "C2"
## CRUK0041 CRUK0072 CRUK0002 CRUK0032 CRUK0043 CRUK0045 CRUK0084 CRUK0055
## "C2" "C2" "C1" "C1" "C1" "C1" "C1" "C1"
## CRUK0094 CRUK0085 CRUK0057 CRUK0056 CRUK0095 CRUK0033 CRUK0046 CRUK0013
## "C1" "C1" "C1" "C1" "C1" "C1" "C1" "C1"
## CRUK0061 CRUK0050 CRUK0047 CRUK0024 CRUK0060 CRUK0008 CRUK0031 CRUK0073
## "C1" "C1" "C1" "C1" "C1" "C1" "C1" "C1"
## CRUK0016 CRUK0066 CRUK0081 CRUK0090 CRUK0091 CRUK0093 CRUK0100 CRUK0011
## "C5" "C5" "C5" "C5" "C5" "C5" "C5" "C4"
## CRUK0042 CRUK0044 CRUK0059 CRUK0038 CRUK0096 CRUK0040 CRUK0034 CRUK0037
## "C4" "C4" "C4" "C4" "C4" "C4" "C4" "C4"
## CRUK0018 CRUK0039 CRUK0023 CRUK0036 CRUK0089 CRUK0092 CRUK0071 CRUK0078
## "C4" "C4" "C4" "C6" "C6" "C6" "C6" "C6"
## CRUK0083 CRUK0075 CRUK0063 CRUK0067 CRUK0005 CRUK0029 CRUK0035 CRUK0088
## "C6" "C6" "C10" "C10" "C3" "C3" "C3" "C3"
## CRUK0097 CRUK0098 CRUK0064 CRUK0086 CRUK0069 CRUK0009 CRUK0070 CRUK0006
## "C3" "C3" "C3" "C3" "C3" "C3" "C3" "C3"
## CRUK0077 CRUK0099 CRUK0017 CRUK0062 CRUK0065 CRUK0087 CRUK0074 CRUK0068
## "C3" "C3" "C3" "C8" "C8" "C8" "C8" "C8"
## CRUK0076 CRUK0079 CRUK0082 CRUK0014 CRUK0027 CRUK0025 CRUK0030 CRUK0052
## "C9" "C9" "C9" "C7" "C7" "C7" "C7" "C7"
## CRUK0020 CRUK0049 CRUK0051
## "C7" "C11" "C11"
##
##
##
## attr(,"class")
## [1] "rev_cohort_fit"
## attr(,"call")
## revolver_cohort(dataset = subset_data, ONLY.DRIVER = T, MIN.CLUSTER.SIZE = 0)
Access patient-level data
Note Since the new release of REVOLVER, we have implemented the
internal structure of the objects using the tidy data.frame
representations from tidyverse. Most
functions now return tibble data.frames that can be processed with the
dplyr jargon.
Getters
We have made available several types of getters to perform queries on
the data. Getter functions for the data have a common parametrization;
for instance getter functionDrivers takes as input
xa REVOLVER cohort object;patientsa list of patients IDs that will be used to subset the outputs (all by default);
# Access all data for a patient
Data(TRACERx_NEJM_2017_REVOLVER, 'CRUK0001')
## # A tibble: 7 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0001 NF1 TRUE FALSE 1 1
## 2 __mu… CRUK… CRUK0001 ARHGAP35 TRUE FALSE 2 1
## 3 __mu… CRUK… CRUK0001 TP53 TRUE TRUE 3 4
## 4 __mu… CRUK… CRUK0001 MGA TRUE TRUE 3 4
## 5 __mu… CRUK… CRUK0001 WRN TRUE TRUE 3 4
## 6 __mu… Anno… CRUK0001 EGFR TRUE TRUE 3 4
## 7 __mu… CRUK… CRUK0001 PASK TRUE FALSE 5 1
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>
# Access only the drivers for a patient
Drivers(TRACERx_NEJM_2017_REVOLVER, 'CRUK0001')
## # A tibble: 7 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0001 NF1 TRUE FALSE 1 1
## 2 __mu… CRUK… CRUK0001 ARHGAP35 TRUE FALSE 2 1
## 3 __mu… CRUK… CRUK0001 TP53 TRUE TRUE 3 4
## 4 __mu… CRUK… CRUK0001 MGA TRUE TRUE 3 4
## 5 __mu… CRUK… CRUK0001 WRN TRUE TRUE 3 4
## 6 __mu… Anno… CRUK0001 EGFR TRUE TRUE 3 4
## 7 __mu… CRUK… CRUK0001 PASK TRUE FALSE 5 1
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>
# Access the names of the samples for a patient
Samples(TRACERx_NEJM_2017_REVOLVER, 'CRUK0001')
## [1] "R1" "R2" "R3"
# Get the list of truncal (i.e., clonal) mutations in a patient
Truncal(TRACERx_NEJM_2017_REVOLVER, 'CRUK0001')
## # A tibble: 4 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0001 TP53 TRUE TRUE 3 4
## 2 __mu… CRUK… CRUK0001 MGA TRUE TRUE 3 4
## 3 __mu… CRUK… CRUK0001 WRN TRUE TRUE 3 4
## 4 __mu… Anno… CRUK0001 EGFR TRUE TRUE 3 4
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>
# Get the list of subclonal mutations in a patient
Subclonal(TRACERx_NEJM_2017_REVOLVER, 'CRUK0001')
## # A tibble: 3 x 12
## id Misc patientID variantID is.driver is.clonal cluster cluster_size
## <chr> <chr> <chr> <chr> <lgl> <lgl> <chr> <int>
## 1 __mu… CRUK… CRUK0001 NF1 TRUE FALSE 1 1
## 2 __mu… CRUK… CRUK0001 ARHGAP35 TRUE FALSE 2 1
## 3 __mu… CRUK… CRUK0001 PASK TRUE FALSE 5 1
## # … with 4 more variables: CCF <chr>, R1 <dbl>, R2 <dbl>, R3 <dbl>
# Return the CCF entry for all the mutations of a patient,
CCF(TRACERx_NEJM_2017_REVOLVER, 'CRUK0001')
## # A tibble: 7 x 8
## id variantID is.driver is.clonal cluster R1 R2 R3
## <chr> <chr> <lgl> <lgl> <chr> <dbl> <dbl> <dbl>
## 1 __mut_id_756 NF1 TRUE FALSE 1 0.86 0 0
## 2 __mut_id_1225 ARHGAP35 TRUE FALSE 2 0.19 0 0.95
## 3 __mut_id_1350 TP53 TRUE TRUE 3 0.99 0.99 1
## 4 __mut_id_1466 MGA TRUE TRUE 3 0.99 0.99 1
## 5 __mut_id_1519 WRN TRUE TRUE 3 0.97 0.98 0.99
## 6 __mut_id_1540 EGFR TRUE TRUE 3 0.99 0.99 1
## 7 __mut_id_1796 PASK TRUE FALSE 5 0.82 0 0.71
# Return the CCF entry for all the clones of a patient, the overall CCF
# values are obtained by REVOLVER from the average of CCF values across clones.
CCF_clusters(TRACERx_NEJM_2017_REVOLVER, 'CRUK0001')
## # A tibble: 4 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 3 4 TRUE TRUE 0.99 0.99 1
## 2 1 1 TRUE FALSE 0.86 0 0
## 3 2 1 TRUE FALSE 0.19 0 0.95
## 4 5 1 TRUE FALSE 0.82 0 0.71
Summary statistics for patients’ data
You can get a broad set of summary statistics about the
TRACERx_NEJM_2017_REVOLVER cohort for a custom set of patients. The
statistics that are available in summarised format are patient-level
(mutatational burdern, drivers etc.), and driver-level (frequency,
clonality
etc.).
# This returns patient-level statistics like the number of biopsies, overall mutations, drivers,
# clones with drivers, truncal and subclonal mutations.
#
# This is also synonim to `Stats(TRACERx_NEJM_2017_REVOLVER)`
Stats_cohort(TRACERx_NEJM_2017_REVOLVER)
## # A tibble: 99 x 7
## patientID numBiopsies numMutations numDriverMutati… numClonesWithDr…
## <chr> <int> <int> <int> <int>
## 1 CRUK0001 3 7 7 4
## 2 CRUK0002 3 7 7 4
## 3 CRUK0003 5 4 4 2
## 4 CRUK0004 4 4 4 2
## 5 CRUK0005 4 6 6 2
## 6 CRUK0006 2 6 6 3
## 7 CRUK0007 2 3 3 1
## 8 CRUK0008 2 6 6 2
## 9 CRUK0009 4 7 7 2
## 10 CRUK0010 2 3 3 1
## # … with 89 more rows, and 2 more variables: numTruncalMutations <int>,
## # numSubclonalMutations <int>
# This returns driver-level statistics like the number of times the driver is clonal,
# subclonal, or found in general, and for quantity normalized by cohort size (i.e., the percentage)
Stats_drivers(TRACERx_NEJM_2017_REVOLVER)
## # A tibble: 79 x 7
## variantID numClonal p_clonal numSubclonal p_subclonal N_tot p_tot
## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 TP53 53 0.535 3 0.0303 56 0.566
## 2 KRAS 24 0.242 4 0.0404 28 0.283
## 3 EGFR 21 0.212 1 0.0101 22 0.222
## 4 PIK3CA 20 0.202 1 0.0101 21 0.212
## 5 CDKN2A 14 0.141 0 0 14 0.141
## 6 SOX2 14 0.141 0 0 14 0.141
## 7 KEAP1 12 0.121 0 0 12 0.121
## 8 TERT 11 0.111 2 0.0202 13 0.131
## 9 FGFR1 9 0.0909 0 0 9 0.0909
## 10 STK11 8 0.0808 0 0 8 0.0808
## # … with 69 more rows
The list of all patients in the cohort is accessible as
TRACERx_NEJM_2017_REVOLVER$patients, and these functions can be run on
a smaller subset of
patients.
Stats_cohort(TRACERx_NEJM_2017_REVOLVER, patients = TRACERx_NEJM_2017_REVOLVER$patients[1:5])
## # A tibble: 5 x 7
## patientID numBiopsies numMutations numDriverMutati… numClonesWithDr…
## <chr> <int> <int> <int> <int>
## 1 CRUK0001 3 7 7 4
## 2 CRUK0002 3 7 7 4
## 3 CRUK0003 5 4 4 2
## 4 CRUK0004 4 4 4 2
## 5 CRUK0005 4 6 6 2
## # … with 2 more variables: numTruncalMutations <int>,
## # numSubclonalMutations <int>
Access the trees in the cohort
Trees have getters similar to the data, and getters distinguish from trees before and after the fit.
Note The tree fits might be slightly different from the trees before the fit, because their Informatin Transfer is not expanded. Therefore keep this in mind when comparing trees.
Getters
You can to extract the tree of a patient, before its fit. This can be one specific tree, or all of them at once. Trees before the fit are indexed by their rank, which is obtained from the ordering of the tree scores, which are obtained by the evaluated tree structure before the fit.
These getters, for instance Phylo, take as parameter
xthe cohort object;pthe patient identifier;rankthe rank of the tree to extract;datato decide whether one wants the trees before the fit (trees), or the actual fit treefits.
By logic, if you are asking for the fit trees (data = 'fits'), the
rank parameter is not considered (because there is only 1 tree fit by
REVOLVER).
# Access the top-rank tree for a patient
Phylo(TRACERx_NEJM_2017_REVOLVER, 'CRUK0001', rank = 1)
## [ ctree - ctree rank 1/3 for CRUK0001 ]
##
## # A tibble: 4 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 3 4 TRUE TRUE 0.99 0.99 1
## 2 1 1 TRUE FALSE 0.86 0 0
## 3 2 1 TRUE FALSE 0.19 0 0.95
## 4 5 1 TRUE FALSE 0.82 0 0.71
##
## Tree shape (drivers annotated)
##
## \-GL
## \-3 [R2] :: TP53, MGA, WRN, EGFR
## |-1 :: NF1
## | \-5 :: PASK
## \-2 :: ARHGAP35
##
## Information transfer
##
## GL ---> TP53
## GL ---> MGA
## GL ---> WRN
## GL ---> EGFR
## TP53 ---> NF1
## MGA ---> NF1
## WRN ---> NF1
## EGFR ---> NF1
## TP53 ---> ARHGAP35
## MGA ---> ARHGAP35
## WRN ---> ARHGAP35
## EGFR ---> ARHGAP35
## NF1 ---> PASK
##
## Tree score 0.111111111111111
# Access all trees for a patient. We use CRUK0002 because it has only 3 trees
Phylo(TRACERx_NEJM_2017_REVOLVER, 'CRUK0002', rank = NULL)
## $`1`
## [ ctree - ctree rank 1/2 for CRUK0002 ]
##
## # A tibble: 4 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE FALSE 0 0.92 0
## 2 2 2 TRUE TRUE 0.99 0.98 0.99
## 3 5 1 TRUE FALSE 0.78 0 0
## 4 6 1 TRUE FALSE 0.96 0.03 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-2 :: MET, TERT
## |-6 :: EP300
## | \-5 :: NF1
## \-1 :: RB1, IKZF1, KRAS
##
## Information transfer
##
## MET ---> RB1
## MET ---> IKZF1
## MET ---> KRAS
## TERT ---> RB1
## TERT ---> IKZF1
## TERT ---> KRAS
## GL ---> MET
## GL ---> TERT
## EP300 ---> NF1
## MET ---> EP300
## TERT ---> EP300
##
## Tree score 0.75
##
## $`2`
## [ ctree - ctree rank 2/2 for CRUK0002 ]
##
## # A tibble: 4 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 1 3 TRUE FALSE 0 0.92 0
## 2 2 2 TRUE TRUE 0.99 0.98 0.99
## 3 5 1 TRUE FALSE 0.78 0 0
## 4 6 1 TRUE FALSE 0.96 0.03 0.98
##
## Tree shape (drivers annotated)
##
## \-GL
## \-2 :: MET, TERT
## \-1 :: RB1, IKZF1, KRAS
## \-6 :: EP300
## \-5 :: NF1
##
## Information transfer
##
## MET ---> RB1
## MET ---> IKZF1
## MET ---> KRAS
## TERT ---> RB1
## TERT ---> IKZF1
## TERT ---> KRAS
## GL ---> MET
## GL ---> TERT
## EP300 ---> NF1
## RB1 ---> EP300
## IKZF1 ---> EP300
## KRAS ---> EP300
##
## Tree score 0.0833333333333333
Notice that in the printing of a tree to screen you can immediately see
the Information Transfer (IT) for the driver genes. In general, you can
access the IT of a tree with another getter, which takes as extra
parameter type in order to return either the transfer across drivers,
or across clones annotated in a tree.
# Information Transfer for the drivers, top-ranking tree
ITransfer(TRACERx_NEJM_2017_REVOLVER, "CRUK0001", rank = 1, type = 'drivers')
## # A tibble: 13 x 2
## from to
## <chr> <chr>
## 1 GL TP53
## 2 GL MGA
## 3 GL WRN
## 4 GL EGFR
## 5 TP53 NF1
## 6 MGA NF1
## 7 WRN NF1
## 8 EGFR NF1
## 9 TP53 ARHGAP35
## 10 MGA ARHGAP35
## 11 WRN ARHGAP35
## 12 EGFR ARHGAP35
## 13 NF1 PASK
# Information Transfer for the clones, top-ranking tree
ITransfer(TRACERx_NEJM_2017_REVOLVER, "CRUK0001", rank = 1, type = 'clones')
## # A tibble: 4 x 2
## from to
## <chr> <chr>
## 1 GL 3
## 2 3 1
## 3 3 2
## 4 1 5
Fit trees can be accessed using the data argument. Essentially this is
like before, but does not require specifying a rank parameter.
# Access the fit tree for a patient
Phylo(TRACERx_NEJM_2017_REVOLVER, 'CRUK0001', data = 'fits')
## [ ctree - ctree rank 1/3 for CRUK0001 - Information Transfer expanded via Transfer Learning ]
##
## # A tibble: 4 x 7
## cluster nMuts is.driver is.clonal R1 R2 R3
## <chr> <int> <lgl> <lgl> <dbl> <dbl> <dbl>
## 1 3 4 TRUE TRUE 0.99 0.99 1
## 2 1 1 TRUE FALSE 0.86 0 0
## 3 2 1 TRUE FALSE 0.19 0 0.95
## 4 5 1 TRUE FALSE 0.82 0 0.71
##
## Tree shape (drivers annotated)
##
## \-GL
## \-3 [R2] :: TP53, MGA, WRN, EGFR
## |-1 :: NF1
## | \-5 :: PASK
## \-2 :: ARHGAP35
##
## Information transfer
##
## GL ---> EGFR
## GL ---> WRN
## GL ---> MGA
## EGFR ---> TP53
## WRN ---> TP53
## TP53 ---> NF1
## MGA ---> NF1
## TP53 ---> ARHGAP35
## MGA ---> ARHGAP35
## NF1 ---> PASK
##
## Tree score 0.111111111111111
# Information Transfer for the drivers, top-ranking tree. Notice that this is different
# from the result of the above call, because the transfer after fitting is expanded
ITransfer(TRACERx_NEJM_2017_REVOLVER, "CRUK0001", rank = 1, type = 'drivers', data = 'fits')
## # A tibble: 10 x 2
## from to
## <chr> <chr>
## 1 GL EGFR
## 2 GL WRN
## 3 GL MGA
## 4 EGFR TP53
## 5 WRN TP53
## 6 TP53 NF1
## 7 MGA NF1
## 8 TP53 ARHGAP35
## 9 MGA ARHGAP35
## 10 NF1 PASK
Summary statistics for trees and fits
There are getters for summary statistics that work for trees and fits, with the same principles fo the getters for the data discussed above
# This returns patient-level statistics for the trees available in a patient. The tibble reports
# whether the patient has trees annotated, the total number of trees, their minimum and maximum
# scores mutations and the total number of differnet combinations of Information Transfer for
# the available trees.
Stats_trees(TRACERx_NEJM_2017_REVOLVER)
## # A tibble: 99 x 6
## patientID hasTrees numTrees maxScore minScore combInfTransf
## <chr> <lgl> <int> <dbl> <dbl> <int>
## 1 CRUK0001 TRUE 3 0.111 0.111 3
## 2 CRUK0002 TRUE 2 0.75 0.0833 2
## 3 CRUK0003 TRUE 1 1 1 1
## 4 CRUK0004 TRUE 1 1 1 1
## 5 CRUK0005 TRUE 1 1 1 1
## 6 CRUK0006 TRUE 2 0.667 0.167 2
## 7 CRUK0007 TRUE 1 1 1 1
## 8 CRUK0008 TRUE 1 1 1 1
## 9 CRUK0009 TRUE 1 1 1 1
## 10 CRUK0010 TRUE 1 1 1 1
## # … with 89 more rows
# This returns the same table of above, but with some extended information on the fits (like the fit rank, etc)
Stats_fits(TRACERx_NEJM_2017_REVOLVER)
## # A tibble: 99 x 9
## patientID hasTrees numTrees maxScore minScore combInfTransf Solution
## <chr> <lgl> <int> <dbl> <dbl> <int> <int>
## 1 CRUK0001 TRUE 3 0.111 0.111 3 1
## 2 CRUK0002 TRUE 2 0.75 0.0833 2 1
## 3 CRUK0003 TRUE 1 1 1 1 1
## 4 CRUK0004 TRUE 1 1 1 1 1
## 5 CRUK0005 TRUE 1 1 1 1 1
## 6 CRUK0006 TRUE 2 0.667 0.167 2 1
## 7 CRUK0007 TRUE 1 1 1 1 1
## 8 CRUK0008 TRUE 1 1 1 1 1
## 9 CRUK0009 TRUE 1 1 1 1 1
## 10 CRUK0010 TRUE 1 1 1 1 1
## # … with 89 more rows, and 2 more variables: converged <lgl>,
## # penalty <dbl>
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