tcgaCompare: Compare mutation load against TCGA cohorts
In maftools: Summarize, Analyze and Visualize MAF Files
Description
Usage
Arguments
Details
Value
Source
References
Examples
Description
Compares mutation load in input MAF against all of 33 TCGA cohorts derived from MC3 project.
Usage
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tcgaCompare(
maf,
capture_size = NULL,
tcga_capture_size = 35.8,
cohortName = NULL,
tcga_cohorts = NULL,
primarySite = FALSE,
col = c("gray70", "black"),
bg_col = c("#EDF8B1", "#2C7FB8"),
medianCol = "red",
decreasing = FALSE,
logscale = TRUE,
rm_hyper = FALSE,
rm_zero = TRUE,
cohortFontSize = 0.8,
axisFontSize = 0.8
)
Arguments
maf
MAF object(s) generated by read.maf
capture_size
capture size for input MAF in MBs. Default NULL. If provided plot will be scaled to mutations per mb. TCGA capture size is assumed to be 35.8 mb.
tcga_capture_size
capture size for TCGA cohort in MB. Default 35.8. Do NOT change. See details for more information.
cohortName
name for the input MAF cohort. Default "Input"
tcga_cohorts
restrict tcga data to these cohorts.
primarySite
If TRUE uses primary site of cancer as labels instead of TCGA project IDs. Default FALSE.
col
color vector for length 2 TCGA cohorts and input MAF cohort. Default gray70 and black.
bg_col
background color. Default'#EDF8B1', '#2C7FB8'
medianCol
color for median line. Default red.
decreasing
Default FALSE. Cohorts are arranged in increasing mutation burden.
logscale
Default TRUE
rm_hyper
Remove hyper mutated samples (outliers)? Default FALSE
rm_zero
Remove samples with zero mutations? Default TRUE
cohortFontSize
Default 0.8
axisFontSize
Default 0.8
Details
Tumor mutation burden for TCGA cohorts is obtained from TCGA MC3 study. For consistency TMB is estimated by restricting variants within Agilent Sureselect capture kit of size 35.8 MB.
Value
data.table with median mutations per cohort
Source
TCGA MC3 file was obtained from https://api.gdc.cancer.gov/data/1c8cfe5f-e52d-41ba-94da-f15ea1337efc. See TCGAmutations R package for more details. Further downstream script to estimate TMB for each sample can be found in ‘inst/scripts/estimate_tcga_tmb.R’
References
Scalable Open Science Approach for Mutation Calling of Tumor Exomes Using Multiple Genomic Pipelines Kyle Ellrott, Matthew H. Bailey, Gordon Saksena, et. al. Cell Syst. 2018 Mar 28; 6(3): 271–281.e7. https://doi.org/10.1016/j.cels.2018.03.002
Examples
1
2
3
laml.maf <- system.file("extdata", "tcga_laml.maf.gz", package = "maftools")
laml <- read.maf(maf = laml.maf)
tcgaCompare(maf = laml, cohortName = "AML")
Example output
-Reading
-Validating
-Silent variants: 475
-Summarizing
-Processing clinical data
--Missing clinical data
-Finished in 0.635s elapsed (0.546s cpu)
Performing pairwise t-test for differences in mutation burden..
$median_mutation_burden
Cohort Cohort_Size Median_Mutations Median_Mutations_log10
1: LAML 137 9.0 0.9542425
2: PCPG 183 9.0 0.9542425
3: AML 192 9.0 0.9542425
4: THCA 499 10.0 1.0000000
5: UVM 80 11.5 1.0606978
6: TGCT 133 13.0 1.1139434
7: THYM 123 14.0 1.1461280
8: KICH 66 19.5 1.2900346
9: ACC 92 25.5 1.4065402
10: LGG 524 27.0 1.4313638
11: MESO 82 27.0 1.4313638
12: PRAD 495 27.0 1.4313638
13: PAAD 176 35.0 1.5440680
14: BRCA 1025 40.0 1.6020600
15: SARC 239 40.0 1.6020600
16: CHOL 36 40.5 1.6074550
17: UCS 57 46.0 1.6627578
18: GBM 398 51.0 1.7075702
19: KIRC 370 52.0 1.7160033
20: KIRP 282 65.0 1.8129134
21: OV 411 66.0 1.8195439
22: UCEC 531 75.0 1.8750613
23: LIHC 365 82.0 1.9138139
24: CESC 291 86.0 1.9344985
25: READ 150 88.5 1.9469433
26: ESCA 185 103.0 2.0128372
27: HNSC 509 106.0 2.0253059
28: DLBC 37 110.0 2.0413927
29: STAD 438 114.5 2.0588055
30: COAD 406 115.0 2.0606978
31: BLCA 411 169.0 2.2278867
32: LUAD 516 198.0 2.2966652
33: LUSC 485 229.0 2.3598355
34: SKCM 468 406.5 2.6090605
Cohort Cohort_Size Median_Mutations Median_Mutations_log10
$mutation_burden_perSample
Tumor_Sample_Barcode total cohort
1: TCGA-AB-2808-03B-01W-0728-08 741 LAML
2: TCGA-AB-2828-03B-01W-0728-08 718 LAML
3: TCGA-AB-2826-03B-01W-0728-08 616 LAML
4: TCGA-AB-2806-03B-01W-0728-08 491 LAML
5: TCGA-AB-2833-03B-01W-0728-08 445 LAML
---
10388: TCGA-FR-A2OS-01A-11D-A21A-08 13 SKCM
10389: TCGA-BF-AAP8-01A-11D-A401-08 11 SKCM
10390: TCGA-EB-A4IQ-01A-12D-A25O-08 9 SKCM
10391: TCGA-EB-A4OZ-01A-12D-A25O-08 9 SKCM
10392: TCGA-D3-A8GE-06A-11D-A372-08 6 SKCM
$pairwise_t_test
Cohort1 Cohort2 Pval
1: UCEC BRCA 1.841336e-98
2: UCEC THCA 6.058054e-84
3: UCEC LGG 9.059399e-80
4: UCEC PRAD 4.641347e-79
5: UCEC KIRC 4.898988e-66
---
557: PAAD GBM 9.945562e-01
558: MESO KICH 9.945562e-01
559: THCA TGCT 9.945562e-01
560: UVM TGCT 9.945562e-01
561: UVM THCA 9.945562e-01
Warning message:
In FUN(X[[i]], ...) : Removed 1 samples with zero mutations.
maftools documentation built on Feb. 6, 2021, 2 a.m.
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Description Usage Arguments Details Value Source References Examples
Description
Compares mutation load in input MAF against all of 33 TCGA cohorts derived from MC3 project.
Usage
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | tcgaCompare(
maf,
capture_size = NULL,
tcga_capture_size = 35.8,
cohortName = NULL,
tcga_cohorts = NULL,
primarySite = FALSE,
col = c("gray70", "black"),
bg_col = c("#EDF8B1", "#2C7FB8"),
medianCol = "red",
decreasing = FALSE,
logscale = TRUE,
rm_hyper = FALSE,
rm_zero = TRUE,
cohortFontSize = 0.8,
axisFontSize = 0.8
)
|
Arguments
maf |
|
capture_size |
capture size for input MAF in MBs. Default NULL. If provided plot will be scaled to mutations per mb. TCGA capture size is assumed to be 35.8 mb. |
tcga_capture_size |
capture size for TCGA cohort in MB. Default 35.8. Do NOT change. See details for more information. |
cohortName |
name for the input MAF cohort. Default "Input" |
tcga_cohorts |
restrict tcga data to these cohorts. |
primarySite |
If TRUE uses primary site of cancer as labels instead of TCGA project IDs. Default FALSE. |
col |
color vector for length 2 TCGA cohorts and input MAF cohort. Default gray70 and black. |
bg_col |
background color. Default'#EDF8B1', '#2C7FB8' |
medianCol |
color for median line. Default red. |
decreasing |
Default FALSE. Cohorts are arranged in increasing mutation burden. |
logscale |
Default TRUE |
rm_hyper |
Remove hyper mutated samples (outliers)? Default FALSE |
rm_zero |
Remove samples with zero mutations? Default TRUE |
cohortFontSize |
Default 0.8 |
axisFontSize |
Default 0.8 |
Details
Tumor mutation burden for TCGA cohorts is obtained from TCGA MC3 study. For consistency TMB is estimated by restricting variants within Agilent Sureselect capture kit of size 35.8 MB.
Value
data.table with median mutations per cohort
Source
TCGA MC3 file was obtained from https://api.gdc.cancer.gov/data/1c8cfe5f-e52d-41ba-94da-f15ea1337efc. See TCGAmutations R package for more details. Further downstream script to estimate TMB for each sample can be found in ‘inst/scripts/estimate_tcga_tmb.R’
References
Scalable Open Science Approach for Mutation Calling of Tumor Exomes Using Multiple Genomic Pipelines Kyle Ellrott, Matthew H. Bailey, Gordon Saksena, et. al. Cell Syst. 2018 Mar 28; 6(3): 271–281.e7. https://doi.org/10.1016/j.cels.2018.03.002
Examples
1 2 3 | laml.maf <- system.file("extdata", "tcga_laml.maf.gz", package = "maftools")
laml <- read.maf(maf = laml.maf)
tcgaCompare(maf = laml, cohortName = "AML")
|
Example output
-Reading
-Validating
-Silent variants: 475
-Summarizing
-Processing clinical data
--Missing clinical data
-Finished in 0.635s elapsed (0.546s cpu)
Performing pairwise t-test for differences in mutation burden..
$median_mutation_burden
Cohort Cohort_Size Median_Mutations Median_Mutations_log10
1: LAML 137 9.0 0.9542425
2: PCPG 183 9.0 0.9542425
3: AML 192 9.0 0.9542425
4: THCA 499 10.0 1.0000000
5: UVM 80 11.5 1.0606978
6: TGCT 133 13.0 1.1139434
7: THYM 123 14.0 1.1461280
8: KICH 66 19.5 1.2900346
9: ACC 92 25.5 1.4065402
10: LGG 524 27.0 1.4313638
11: MESO 82 27.0 1.4313638
12: PRAD 495 27.0 1.4313638
13: PAAD 176 35.0 1.5440680
14: BRCA 1025 40.0 1.6020600
15: SARC 239 40.0 1.6020600
16: CHOL 36 40.5 1.6074550
17: UCS 57 46.0 1.6627578
18: GBM 398 51.0 1.7075702
19: KIRC 370 52.0 1.7160033
20: KIRP 282 65.0 1.8129134
21: OV 411 66.0 1.8195439
22: UCEC 531 75.0 1.8750613
23: LIHC 365 82.0 1.9138139
24: CESC 291 86.0 1.9344985
25: READ 150 88.5 1.9469433
26: ESCA 185 103.0 2.0128372
27: HNSC 509 106.0 2.0253059
28: DLBC 37 110.0 2.0413927
29: STAD 438 114.5 2.0588055
30: COAD 406 115.0 2.0606978
31: BLCA 411 169.0 2.2278867
32: LUAD 516 198.0 2.2966652
33: LUSC 485 229.0 2.3598355
34: SKCM 468 406.5 2.6090605
Cohort Cohort_Size Median_Mutations Median_Mutations_log10
$mutation_burden_perSample
Tumor_Sample_Barcode total cohort
1: TCGA-AB-2808-03B-01W-0728-08 741 LAML
2: TCGA-AB-2828-03B-01W-0728-08 718 LAML
3: TCGA-AB-2826-03B-01W-0728-08 616 LAML
4: TCGA-AB-2806-03B-01W-0728-08 491 LAML
5: TCGA-AB-2833-03B-01W-0728-08 445 LAML
---
10388: TCGA-FR-A2OS-01A-11D-A21A-08 13 SKCM
10389: TCGA-BF-AAP8-01A-11D-A401-08 11 SKCM
10390: TCGA-EB-A4IQ-01A-12D-A25O-08 9 SKCM
10391: TCGA-EB-A4OZ-01A-12D-A25O-08 9 SKCM
10392: TCGA-D3-A8GE-06A-11D-A372-08 6 SKCM
$pairwise_t_test
Cohort1 Cohort2 Pval
1: UCEC BRCA 1.841336e-98
2: UCEC THCA 6.058054e-84
3: UCEC LGG 9.059399e-80
4: UCEC PRAD 4.641347e-79
5: UCEC KIRC 4.898988e-66
---
557: PAAD GBM 9.945562e-01
558: MESO KICH 9.945562e-01
559: THCA TGCT 9.945562e-01
560: UVM TGCT 9.945562e-01
561: UVM THCA 9.945562e-01
Warning message:
In FUN(X[[i]], ...) : Removed 1 samples with zero mutations.
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