README.md
In mrkbrtkhn/cTagPipe:
cTagePipe_readme
About cTagPipe
This application aims at the identification of DNA sequences that allow
the C-terminal tagging of endogenous loci in order to express fusion
proteins. To achieve this, a combination of CRISPR/Cas9-mediated
induction of DNA breaks and homologous recombination mediated repair
with engineered repair templates is applied.
The application mainly works as a Shiny app but can be run from the R
command line, too. The user selects the gene of interest and the
pipeline calculates CRISPR guide RNAs, selects recombination templates
and modifies/mutates the templates if required as such, that the guide
RNAs will not be able to allow cutting of the recombined locus.
Installation
Please install the latest version of R from https://www.r-project.org.
On Ubuntu you will have to install a number of system packages in order
to make the subsequent installation of R packages possible.
sudo apt-get install libssl-dev
sudo apt-get install libcurl4-openssl-dev
sudo apt-get install libxml2-dev
In order to install this package, you require R’s devtools:
listOfPackages <- c("devtools")
newPackages <- listOfPackages[!(listOfPackages %in% installed.packages()[,"Package"])]
if (length(newPackages)>0) {
source("https://bioconductor.org/biocLite.R")
install.packages(newPackages)
}
This enables you to install directly from GitHub repository:
install_github("mrkbrtkhn/cTagPipe")
Most likely this will produce a lot of errors. Dependencies are still a
mess and I currently have no time to work on them. Please install them
manually.
Running cTagPipe functionality:
Assuming you have managed to install cTagPipe, the following code will
start a Shiny server with the functionality as it is yet implemented:
library(cTagPipeTest)
distanceBetweenGuides <- 100
recArmLength<-150
removeAddGeneHits <- TRUE
browserWindow<-200
### target sequences
seqs<-readDNAStringSet(system.file('extdata','rec_sequences.fa',package='cTagPipeTest'))
mAID <- seqs$mAID
tripleFlag<- seqs$triple_FLAG
t2A<- seqs$t2A
fiveP<- seqs$`5_prime_PITCH`
threeP<- seqs$`3_prime_PITCH`
neoM<- seqs$NeomycinR
hygM<- seqs$HygromycinR
### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ###
### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ###
### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ###
## Only run examples in interactive R sessions
if (interactive()) {
ui <- shiny::fluidPage(
shiny::pageWithSidebar(
shiny::headerPanel('C-terminal tagging pipeline'),
shiny::sidebarPanel(
shiny::selectInput('myGene', 'Transcript ID', c("NM_001304504","NM_153252","NM_001273",
"NM_000237","NM_002106","NM_138635","NM_014660",
"NM_175061","NM_030665","NM_005650","NM_001141969",
"NM_003325","NM_003496","NM_014034","NM_020713",
"NM_001203258","NM_004689","NM_006565","NM_080618",
"NM_002875","NM_133487","NM_003883","NM_021975",
"NM_001077700","NM_052927","NM_012308","NM_000937",
"NM_001004456","NM_001278215",
"NM_001077700","NM_005349")),
shiny::selectInput('myGenome', 'Genome', c("hg38")),
shiny::numericInput('winSize', 'Window Size', 100, min = 50, max = 150),
shiny::selectInput('myCassette', 'Rec. template', c("PITCH/homolgy_arm/AID/tripleFLAG/T2A/homolgy_arm/PITCH")),
shiny::actionButton('run', 'Run'),
width = 3
),
shiny::mainPanel(#width=800,
shiny::tabsetPanel(
shiny::tabPanel("Analysis report",shiny::verbatimTextOutput("testout")),
shiny::tabPanel("Plot", shiny::plotOutput("plot1")),
shiny::tabPanel("CCTop summary", DT::dataTableOutput("ccSumTable", width = 800)),
shiny::tabPanel("CCTop results", DT::dataTableOutput("ccbindTable", width = 800)),
shiny::tabPanel("Guide pairs", DT::dataTableOutput("pairwiseSelections", width = 800)),
shiny::tabPanel("Alignment test", msaR::msaROutput("msa", width="100%")),
shiny::tabPanel("Sequences", shiny::verbatimTextOutput("seqSummary")),
shiny::tabPanel("Mutation view guide 1", DT::dataTableOutput("mutView1", width = 1000)),
shiny::tabPanel("Mutation view guide 2", DT::dataTableOutput("mutView2", width = 1000))
)
)))
shiny::shinyApp(ui, server)
}
Session Information
sessionInfo()
## R version 3.4.0 (2017-04-21)
## Platform: x86_64-apple-darwin15.6.0 (64-bit)
## Running under: macOS 10.13.6
##
## Matrix products: default
## BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRlapack.dylib
##
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
##
## attached base packages:
## [1] grid stats4 parallel stats graphics grDevices utils
## [8] datasets methods base
##
## other attached packages:
## [1] cTagPipeTest_0.1.0 roxygen2_6.1.1.9000
## [3] knitr_1.21 rmarkdown_1.11
## [5] BSgenome.Hsapiens.UCSC.hg38_1.4.1 BSgenome_1.44.0
## [7] Gviz_1.20.0 org.Hs.eg.db_3.4.1
## [9] shiny_1.2.0 GenomicFeatures_1.28.0
## [11] AnnotationDbi_1.38.2 Biobase_2.36.2
## [13] rtracklayer_1.36.6 GenomicRanges_1.28.2
## [15] GenomeInfoDb_1.12.0 seqinr_3.4-5
## [17] msaR_0.3.0 msa_1.8.0
## [19] Biostrings_2.44.0 XVector_0.16.0
## [21] IRanges_2.10.5 S4Vectors_0.14.7
## [23] BiocGenerics_0.22.1 DT_0.5
## [25] RCurl_1.95-4.12 bitops_1.0-6
## [27] devtools_1.13.1
##
## loaded via a namespace (and not attached):
## [1] colorspace_1.3-2 biovizBase_1.24.0
## [3] htmlTable_1.9 base64enc_0.1-3
## [5] dichromat_2.0-0 rstudioapi_0.9.0
## [7] bit64_0.9-7 interactiveDisplayBase_1.14.0
## [9] xml2_1.2.0 splines_3.4.0
## [11] ade4_1.7-13 jsonlite_1.6
## [13] Formula_1.2-1 Rsamtools_1.28.0
## [15] cluster_2.0.6 compiler_3.4.0
## [17] httr_1.3.1 backports_1.1.3
## [19] assertthat_0.2.0 Matrix_1.2-10
## [21] lazyeval_0.2.0 later_0.8.0
## [23] acepack_1.4.1 htmltools_0.3.6
## [25] prettyunits_1.0.2 tools_3.4.0
## [27] gtable_0.2.0 GenomeInfoDbData_0.99.0
## [29] Rcpp_1.0.0 ape_5.1
## [31] nlme_3.1-131 crosstalk_1.0.0
## [33] xfun_0.4 stringr_1.4.0
## [35] mime_0.5 ensembldb_2.0.1
## [37] XML_3.98-1.16 AnnotationHub_2.8.1
## [39] zlibbioc_1.22.0 MASS_7.3-47
## [41] scales_0.4.1 VariantAnnotation_1.22.0
## [43] BiocInstaller_1.26.1 hms_0.3
## [45] promises_1.0.1 ProtGenerics_1.8.0
## [47] SummarizedExperiment_1.6.1 AnnotationFilter_1.0.0
## [49] RColorBrewer_1.1-2 yaml_2.2.0
## [51] curl_2.6 memoise_1.1.0
## [53] gridExtra_2.2.1 ggplot2_2.2.1
## [55] biomaRt_2.39.2 rpart_4.1-11
## [57] latticeExtra_0.6-28 stringi_1.3.1
## [59] RSQLite_2.1.1 checkmate_1.8.2
## [61] BiocParallel_1.10.1 commonmark_1.7
## [63] rlang_0.3.1 pkgconfig_2.0.2
## [65] matrixStats_0.52.2 evaluate_0.10
## [67] lattice_0.20-35 GenomicAlignments_1.12.1
## [69] htmlwidgets_1.3 bit_1.1-14
## [71] plyr_1.8.4 magrittr_1.5
## [73] R6_2.4.0 Hmisc_4.0-3
## [75] DelayedArray_0.2.3 DBI_1.0.0
## [77] pillar_1.1.0 foreign_0.8-68
## [79] withr_2.1.2 survival_2.41-3
## [81] nnet_7.3-12 tibble_1.4.2
## [83] crayon_1.3.4 progress_1.2.0
## [85] data.table_1.12.0 blob_1.1.1
## [87] git2r_0.18.0 digest_0.6.18
## [89] xtable_1.8-2 httpuv_1.4.5.1
## [91] munsell_0.4.3
mrkbrtkhn/cTagPipe documentation built on May 31, 2021, 11:25 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
cTagePipe_readme
About cTagPipe
This application aims at the identification of DNA sequences that allow the C-terminal tagging of endogenous loci in order to express fusion proteins. To achieve this, a combination of CRISPR/Cas9-mediated induction of DNA breaks and homologous recombination mediated repair with engineered repair templates is applied.
The application mainly works as a Shiny app but can be run from the R command line, too. The user selects the gene of interest and the pipeline calculates CRISPR guide RNAs, selects recombination templates and modifies/mutates the templates if required as such, that the guide RNAs will not be able to allow cutting of the recombined locus.
Installation
Please install the latest version of R from https://www.r-project.org. On Ubuntu you will have to install a number of system packages in order to make the subsequent installation of R packages possible.
sudo apt-get install libssl-dev
sudo apt-get install libcurl4-openssl-dev
sudo apt-get install libxml2-dev
In order to install this package, you require R’s devtools:
listOfPackages <- c("devtools")
newPackages <- listOfPackages[!(listOfPackages %in% installed.packages()[,"Package"])]
if (length(newPackages)>0) {
source("https://bioconductor.org/biocLite.R")
install.packages(newPackages)
}
This enables you to install directly from GitHub repository:
install_github("mrkbrtkhn/cTagPipe")
Most likely this will produce a lot of errors. Dependencies are still a mess and I currently have no time to work on them. Please install them manually.
Running cTagPipe functionality:
Assuming you have managed to install cTagPipe, the following code will start a Shiny server with the functionality as it is yet implemented:
library(cTagPipeTest)
distanceBetweenGuides <- 100
recArmLength<-150
removeAddGeneHits <- TRUE
browserWindow<-200
### target sequences
seqs<-readDNAStringSet(system.file('extdata','rec_sequences.fa',package='cTagPipeTest'))
mAID <- seqs$mAID
tripleFlag<- seqs$triple_FLAG
t2A<- seqs$t2A
fiveP<- seqs$`5_prime_PITCH`
threeP<- seqs$`3_prime_PITCH`
neoM<- seqs$NeomycinR
hygM<- seqs$HygromycinR
### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ###
### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ###
### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ###
## Only run examples in interactive R sessions
if (interactive()) {
ui <- shiny::fluidPage(
shiny::pageWithSidebar(
shiny::headerPanel('C-terminal tagging pipeline'),
shiny::sidebarPanel(
shiny::selectInput('myGene', 'Transcript ID', c("NM_001304504","NM_153252","NM_001273",
"NM_000237","NM_002106","NM_138635","NM_014660",
"NM_175061","NM_030665","NM_005650","NM_001141969",
"NM_003325","NM_003496","NM_014034","NM_020713",
"NM_001203258","NM_004689","NM_006565","NM_080618",
"NM_002875","NM_133487","NM_003883","NM_021975",
"NM_001077700","NM_052927","NM_012308","NM_000937",
"NM_001004456","NM_001278215",
"NM_001077700","NM_005349")),
shiny::selectInput('myGenome', 'Genome', c("hg38")),
shiny::numericInput('winSize', 'Window Size', 100, min = 50, max = 150),
shiny::selectInput('myCassette', 'Rec. template', c("PITCH/homolgy_arm/AID/tripleFLAG/T2A/homolgy_arm/PITCH")),
shiny::actionButton('run', 'Run'),
width = 3
),
shiny::mainPanel(#width=800,
shiny::tabsetPanel(
shiny::tabPanel("Analysis report",shiny::verbatimTextOutput("testout")),
shiny::tabPanel("Plot", shiny::plotOutput("plot1")),
shiny::tabPanel("CCTop summary", DT::dataTableOutput("ccSumTable", width = 800)),
shiny::tabPanel("CCTop results", DT::dataTableOutput("ccbindTable", width = 800)),
shiny::tabPanel("Guide pairs", DT::dataTableOutput("pairwiseSelections", width = 800)),
shiny::tabPanel("Alignment test", msaR::msaROutput("msa", width="100%")),
shiny::tabPanel("Sequences", shiny::verbatimTextOutput("seqSummary")),
shiny::tabPanel("Mutation view guide 1", DT::dataTableOutput("mutView1", width = 1000)),
shiny::tabPanel("Mutation view guide 2", DT::dataTableOutput("mutView2", width = 1000))
)
)))
shiny::shinyApp(ui, server)
}
Session Information
sessionInfo()
## R version 3.4.0 (2017-04-21)
## Platform: x86_64-apple-darwin15.6.0 (64-bit)
## Running under: macOS 10.13.6
##
## Matrix products: default
## BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRlapack.dylib
##
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
##
## attached base packages:
## [1] grid stats4 parallel stats graphics grDevices utils
## [8] datasets methods base
##
## other attached packages:
## [1] cTagPipeTest_0.1.0 roxygen2_6.1.1.9000
## [3] knitr_1.21 rmarkdown_1.11
## [5] BSgenome.Hsapiens.UCSC.hg38_1.4.1 BSgenome_1.44.0
## [7] Gviz_1.20.0 org.Hs.eg.db_3.4.1
## [9] shiny_1.2.0 GenomicFeatures_1.28.0
## [11] AnnotationDbi_1.38.2 Biobase_2.36.2
## [13] rtracklayer_1.36.6 GenomicRanges_1.28.2
## [15] GenomeInfoDb_1.12.0 seqinr_3.4-5
## [17] msaR_0.3.0 msa_1.8.0
## [19] Biostrings_2.44.0 XVector_0.16.0
## [21] IRanges_2.10.5 S4Vectors_0.14.7
## [23] BiocGenerics_0.22.1 DT_0.5
## [25] RCurl_1.95-4.12 bitops_1.0-6
## [27] devtools_1.13.1
##
## loaded via a namespace (and not attached):
## [1] colorspace_1.3-2 biovizBase_1.24.0
## [3] htmlTable_1.9 base64enc_0.1-3
## [5] dichromat_2.0-0 rstudioapi_0.9.0
## [7] bit64_0.9-7 interactiveDisplayBase_1.14.0
## [9] xml2_1.2.0 splines_3.4.0
## [11] ade4_1.7-13 jsonlite_1.6
## [13] Formula_1.2-1 Rsamtools_1.28.0
## [15] cluster_2.0.6 compiler_3.4.0
## [17] httr_1.3.1 backports_1.1.3
## [19] assertthat_0.2.0 Matrix_1.2-10
## [21] lazyeval_0.2.0 later_0.8.0
## [23] acepack_1.4.1 htmltools_0.3.6
## [25] prettyunits_1.0.2 tools_3.4.0
## [27] gtable_0.2.0 GenomeInfoDbData_0.99.0
## [29] Rcpp_1.0.0 ape_5.1
## [31] nlme_3.1-131 crosstalk_1.0.0
## [33] xfun_0.4 stringr_1.4.0
## [35] mime_0.5 ensembldb_2.0.1
## [37] XML_3.98-1.16 AnnotationHub_2.8.1
## [39] zlibbioc_1.22.0 MASS_7.3-47
## [41] scales_0.4.1 VariantAnnotation_1.22.0
## [43] BiocInstaller_1.26.1 hms_0.3
## [45] promises_1.0.1 ProtGenerics_1.8.0
## [47] SummarizedExperiment_1.6.1 AnnotationFilter_1.0.0
## [49] RColorBrewer_1.1-2 yaml_2.2.0
## [51] curl_2.6 memoise_1.1.0
## [53] gridExtra_2.2.1 ggplot2_2.2.1
## [55] biomaRt_2.39.2 rpart_4.1-11
## [57] latticeExtra_0.6-28 stringi_1.3.1
## [59] RSQLite_2.1.1 checkmate_1.8.2
## [61] BiocParallel_1.10.1 commonmark_1.7
## [63] rlang_0.3.1 pkgconfig_2.0.2
## [65] matrixStats_0.52.2 evaluate_0.10
## [67] lattice_0.20-35 GenomicAlignments_1.12.1
## [69] htmlwidgets_1.3 bit_1.1-14
## [71] plyr_1.8.4 magrittr_1.5
## [73] R6_2.4.0 Hmisc_4.0-3
## [75] DelayedArray_0.2.3 DBI_1.0.0
## [77] pillar_1.1.0 foreign_0.8-68
## [79] withr_2.1.2 survival_2.41-3
## [81] nnet_7.3-12 tibble_1.4.2
## [83] crayon_1.3.4 progress_1.2.0
## [85] data.table_1.12.0 blob_1.1.1
## [87] git2r_0.18.0 digest_0.6.18
## [89] xtable_1.8-2 httpuv_1.4.5.1
## [91] munsell_0.4.3
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.