First Commit

cn.mops.R

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+###################
+##   cn.mops     ## 
+##  Jiyang Zhang ##
+##  2019.01.21   ##
+###################
+#
+#1 Introduction
+##The cn.mops package is part of the Bioconductor (http://www.bioconductor.org) project.
+##The package allows to detect copy number variations (CNVs) from next generation sequencing (NGS) data sets based on a generative model. 
+##Please visit http://www.bioinf.jku.at/software/cnmops/cnmops.htmlfor additional information.
+#
+#2 Set up
+#
+##2.1 load package
+library(cn.mops)
+#
+##2.2 load options
+#
+###2.2.1 Collect arguments
+args <- commandArgs(TRUE)
+#
+###2.2.2 Help section
+#### Default setting when no arguments passed
+if(length(args) < 1) {
+  args <- c("--help")
+}
+#### Help section
+if("--help" %in% args) {
+  cat("
+      The R Script
+      
+      Arguments:
+      --Tumor=the name of the TUMOR sample BAMfile - string
+      --Normal=the name of the NORMAL sample BAMfile - string
+	  --TumorSampleID=the name of the TUMOR sample  - string
+      --bed_file=BED (Browser Extensible Data) lines have four required fields included chr, start, end and gene annotation.  - string
+      --workDir=working directory   - character
+      --outputDir=where you want to output the pictures - character
+      --help              - print this text
+      
+      
+      Example:
+      Rscript cn.mops.R --Tumor=TumorSample.bam --Normal=NormalSample.bam --TumorSampleID=TumorSampleID --bed_file=bedFile --workDir=./ --outputDir=./ \n\n")
+  
+  q(save="no")
+}
+#
+####2.2.3 Parse arguments (we expect the form --arg=value)
+parseArgs <- function(x) strsplit(sub("^--", "", x), "=")
+argsDF <- as.data.frame(do.call("rbind", parseArgs(args)))
+argsL <- as.list(as.character(argsDF$V2))
+names(argsL) <- argsDF$V1
+args<-argsL
+#
+## Arg1 default
+if(is.null(args$Tumor)) {
+  stop("Tumor sample bamFile is missing")
+}else{
+  Tumor=args$Tumor
+}
+#
+## Arg2 default
+if(is.null(args$Normal)) {
+  stop("Normal sample bamFileis missing")
+}else{
+  Normal=args$Normal
+}
+#
+## Arg3 default
+if(is.null(args$TumorSampleID)) {
+  stop("TumorSampleID missing")
+}else{
+ TumorSampleID=args$TumorSampleID
+}
+#
+## Arg4 default
+if(is.null(args$bed_file)) {
+  stop("bed_file is missing")
+}else{
+  bed_file=args$bed_file
+}
+#
+## Arg5 default
+if(is.null(args$workDir)) {
+  stop("workDir is missing")
+}else{
+  workDir=args$workDir
+}
+#
+## Arg6 default
+if(is.null(args$outputDir)) {
+  stop("outputDir is missing")
+}else{
+  outputDir=args$outputDir
+}
+#
+#3 Run cn.mops
+# Tumor <- c("Illumina_pt2_B1700.chr20_X.sorted.deduped.bam")
+# Normal <- c("Illumina_pt2_B17NC.chr20_X.sorted.deduped.bam")
+# workDir <- "/home/zhangjiyang/shiJzhiP/shijianzhiP2/scripts"
+# outputDir <- "/home/zhangjiyang/shiJzhiP/shijianzhiP2/scripts"
+# bed_file <- "Illumina_pt2_exonanno_exonfrom1_chr20_X.bed"
+#
+##3.1 BAM files and bed file as input.
+BAMFiles <- c(Tumor,Normal)
+segments <- read.table(paste0(workDir,"/", bed_file),sep="\t",as.is=TRUE)
+#
+##3.2 Get read counts from BAM.
+gr <- GRanges(segments[,1],IRanges(segments[,2],segments[,3]))
+#
+##3.3 The result object
+sample <- getSegmentReadCountsFromBAM(BAMFiles,GR=gr,mode="paired")
+resRef <- referencecn.mops(cases=sample[,1],controls=sample[,2],
+                           classes=c("CN0", "CN1", "CN2", "CN3", "CN4", "CN5", "CN6",
+                                     "CN7","CN8","CN16","CN32","CN64","CN128"),
+                           I = c(0.025, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 8, 16, 32, 64),
+                           segAlgorithm="DNAcopy")
+result<- calcIntegerCopyNumbers(resRef)
+CNVs <- as.data.frame(cnvs(result))
+colnames(segments) <- c("chr","start","end","anno")
+colnames(CNVs)[colnames(CNVs)=="seqnames"]  <- c("chr")
+bed.anno <- segments
+bed.anno$start_idx <- paste(bed.anno$chr,bed.anno$start,sep="_")
+bed.anno$end_idx <- paste(bed.anno$chr,bed.anno$end,sep="_")
+CNV_number <- nrow(CNVs)
+Res <- data.frame()
+for(i in 1:CNV_number) {
+  CNVs.start.idx <- paste(CNVs[i,]$chr,CNVs[i,]$start,sep="_")
+  CNVs.end.idx <- paste(CNVs[i,]$chr,CNVs[i,]$end,sep="_")
+  exon_start <- rownames(bed.anno[bed.anno$start_idx%in%CNVs.start.idx,])
+  exon_end <- rownames(bed.anno[bed.anno$end_idx%in%CNVs.end.idx,])
+  res <- CNVs[i,]
+  res$gene <- unlist(strsplit(bed.anno[exon_start,]$anno,split = "_"))[1]
+  res$exon_start <- unlist(strsplit(bed.anno[exon_start,]$anno,split = "_"))[2]
+  res$exon_end <-  unlist(strsplit(bed.anno[exon_end,]$anno,split = "_"))[2]
+  Res <- rbind(Res,res)
+}
+Res <- data.frame(sampleName=Res$sampleName,chr=Res$chr,
+                  start=Res$start,end=Res$end,gene=Res$gene,
+                  exon_start=Res$exon_start,exon_end=Res$exon_end,
+                  CN=Res$CN)
+#
+##3.4 Output
+write.table(Res,paste0(outputDir,"/",TumorSampleID,"cn.mops.res.txt"),sep="\t",
+           col.names=T,row.names=F,quote=F)
+
+

inputs

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+{
+  "{{ project_name }}.TumorBam": "{{ TumorBam }}",
+  "{{ project_name }}.TumorSampleID": "{{ TumorSampleID }}",
+  "{{ project_name }}.outputDir": "{{ outputDir }}",
+  "{{ project_name }}.docker": "{{ docker }}",
+  "{{ project_name }}.cluster_config": "{{ cluster_config }}",
+  "{{ project_name }}.workDir": "{{ workDir }}",
+  "{{ project_name }}.NormalBam": "{{ NormalBam }}",
+  "{{ project_name }}.disk_size": "{{ disk_size }}",
+  "{{ project_name }}.bed_file": "{{ bed_file }}"
+}
+

tasks/cn_mops.wdl

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+task CNV {
+	String TumorBam
+	String NormalBam
+	String TumorSampleID
+	String bed_file
+	String workDir
+	String outputDir
+	String docker
+	String disk_size
+	String cluster_config
+	
+	command <<<
+		Rscript cn.mops.R --Tumor=${TumorBam} --Normal=${NormalBam} --TumorID==${TumorSampleID} --bed_file=${bed_file} --workDir=${workDir} --outputDir=${outputDir}
+	>>>
+
+	runtime {
+		docker: docker
+    	cluster: cluster_config
+    	systemDisk: "cloud_ssd 40"
+    	dataDisk: "cloud_ssd " + disk_size + " /cromwell_root/"
+	}
+	output {
+		File sorted_bam = "${TumorSampleID}.cn.mops.res.txt"
+	}
+}

workflow.wdl

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+import "./tasks/cn_mops.wdl" as CNV
+
+workflow {{project_name}} {
+
+	String TumorBam
+	String NormalBam
+	String TumorSampleID
+	String bed_file
+	String workDir
+	String outputDir
+	String docker
+	String disk_size
+	String cluster_config
+
+	call CNV.CNV as CNV {
+		input: 
+			TumorBam=TumorBam,
+			NormalBam=NormalBam,
+			TumorSampleID=TumorSampleID,
+			bed_file=bed_file,
+			workDir=workDir,
+			outputDir=outputDir,
+			docker=docker,
+			disk_size=disk_size,
+			cluster_config=cluster_config
+	}
+}