mirror of
https://github.com/MillironX/nf-core_modules.git
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7daba6a13f
* add unzip alleles + loci * fix the partial absolute prefix path * exchanged deprecated function + added metrics * updated meta * tested logRCorrection + cram input * added BED for WES * added outputs + alleleCounter version * test samtools chr operations, fixed cancerit conda * ch formatting, fasta, bed input * comment out local tests * added metrics, bed, ref_fasta * rm print statement * added stub outputs * rm versions.yml * fix linting * rm fictitious md5sums for stub-run * try fixing top-level of stub versions.yml * ordered inputs alphabetically, ref_fasta -> fasta * rm R system command, adjust meta.yml * prettier yml
196 lines
8.4 KiB
Text
196 lines
8.4 KiB
Text
process ASCAT {
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tag "$meta.id"
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label 'process_medium'
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conda (params.enable_conda ? "bioconda::ascat=3.0.0 bioconda::cancerit-allelecount=4.3.0" : null)
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container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ?
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'https://depot.galaxyproject.org/singularity/mulled-v2-c278c7398beb73294d78639a864352abef2931ce:dfe5aaa885de434adb2b490b68972c5840c6d761-0':
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'quay.io/biocontainers/mulled-v2-c278c7398beb73294d78639a864352abef2931ce:dfe5aaa885de434adb2b490b68972c5840c6d761-0' }"
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input:
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tuple val(meta), path(input_normal), path(index_normal), path(input_tumor), path(index_tumor)
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path(allele_files)
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path(loci_files)
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path(bed_file) // optional
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path(fasta) // optional
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path(gc_file) // optional
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path(rt_file) // optional
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output:
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tuple val(meta), path("*png"), emit: png
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tuple val(meta), path("*cnvs.txt"), emit: cnvs
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tuple val(meta), path("*metrics.txt"), emit: metrics
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tuple val(meta), path("*purityploidy.txt"), emit: purityploidy
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tuple val(meta), path("*segments.txt"), emit: segments
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tuple val(meta), path("*alleleFrequencies_chr*.txt"), emit: allelefreqs
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path "versions.yml", emit: versions
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when:
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task.ext.when == null || task.ext.when
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script:
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def args = task.ext.args ?: ''
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def prefix = task.ext.prefix ?: "${meta.id}"
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def gender = args.gender ? "$args.gender" : "NULL"
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def genomeVersion = args.genomeVersion ? "$args.genomeVersion" : "NULL"
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def purity = args.purity ? "$args.purity" : "NULL"
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def ploidy = args.ploidy ? "$args.ploidy" : "NULL"
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def gc_input = gc_file ? "$gc_file" : "NULL"
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def rt_input = rt_file ? "$rt_file" : "NULL"
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def minCounts_arg = args.minCounts ? ",minCounts = $args.minCounts" : ""
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def bed_file_arg = bed_file ? ",BED_file = '$bed_file'": ""
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def chrom_names_arg = args.chrom_names ? ",chrom_names = $args.chrom_names" : ""
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def min_base_qual_arg = args.min_base_qual ? ",min_base_qual = $args.min_base_qual" : ""
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def min_map_qual_arg = args.min_map_qual ? ",min_map_qual = $args.min_map_qual" : ""
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def fasta_arg = fasta ? ",ref.fasta = '$fasta'" : ""
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def skip_allele_counting_tumour_arg = args.skip_allele_counting_tumour ? ",skip_allele_counting_tumour = $args.skip_allele_counting_tumour" : ""
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def skip_allele_counting_normal_arg = args.skip_allele_counting_normal ? ",skip_allele_counting_normal = $args.skip_allele_counting_normal" : ""
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"""
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#!/usr/bin/env Rscript
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library(RColorBrewer)
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library(ASCAT)
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options(bitmapType='cairo')
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#build prefixes: <abspath_to_files/prefix_chr>
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allele_path = normalizePath("$allele_files")
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allele_prefix = paste0(allele_path, "/", "$allele_files", "_chr")
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loci_path = normalizePath("$loci_files")
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loci_prefix = paste0(loci_path, "/", "$loci_files", "_chr")
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#prepare from BAM files
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ascat.prepareHTS(
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tumourseqfile = "$input_tumor",
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normalseqfile = "$input_normal",
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tumourname = "Tumour",
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normalname = "Normal",
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allelecounter_exe = "alleleCounter",
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alleles.prefix = allele_prefix,
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loci.prefix = loci_prefix,
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gender = "$gender",
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genomeVersion = "$genomeVersion",
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nthreads = $task.cpus
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$minCounts_arg
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$bed_file_arg
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$chrom_names_arg
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$min_base_qual_arg
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$min_map_qual_arg
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$fasta_arg
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$skip_allele_counting_tumour_arg
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$skip_allele_counting_normal_arg
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)
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#Load the data
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ascat.bc = ascat.loadData(
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Tumor_LogR_file = "Tumour_tumourLogR.txt",
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Tumor_BAF_file = "Tumour_normalBAF.txt",
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Germline_LogR_file = "Tumour_normalLogR.txt",
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Germline_BAF_file = "Tumour_normalBAF.txt",
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genomeVersion = "$genomeVersion",
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gender = "$gender"
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)
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#Plot the raw data
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ascat.plotRawData(ascat.bc, img.prefix = "Before_correction_")
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# optional LogRCorrection
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if("$gc_input" != "NULL") {
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gc_input = paste0(normalizePath("$gc_input"), "/", "$gc_input", ".txt")
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if("$rt_input" != "NULL"){
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rt_input = paste0(normalizePath("$rt_input"), "/", "$rt_input", ".txt")
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ascat.bc = ascat.correctLogR(ascat.bc, GCcontentfile = gc_input, replictimingfile = rt_input)
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#Plot raw data after correction
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ascat.plotRawData(ascat.bc, img.prefix = "After_correction_GC_")
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}
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else {
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ascat.bc = ascat.correctLogR(ascat.bc, GCcontentfile = gc_input, replictimingfile = $rt_input)
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#Plot raw data after correction
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ascat.plotRawData(ascat.bc, img.prefix = "After_correction_GC_RT_")
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}
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}
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#Segment the data
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ascat.bc = ascat.aspcf(ascat.bc)
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#Plot the segmented data
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ascat.plotSegmentedData(ascat.bc)
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#Run ASCAT to fit every tumor to a model, inferring ploidy, normal cell contamination, and discrete copy numbers
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#If psi and rho are manually set:
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if (!is.null($purity) && !is.null($ploidy)){
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ascat.output <- ascat.runAscat(ascat.bc, gamma=1, rho_manual=$purity, psi_manual=$ploidy)
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} else if(!is.null($purity) && is.null($ploidy)){
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ascat.output <- ascat.runAscat(ascat.bc, gamma=1, rho_manual=$purity)
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} else if(!is.null($ploidy) && is.null($purity)){
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ascat.output <- ascat.runAscat(ascat.bc, gamma=1, psi_manual=$ploidy)
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} else {
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ascat.output <- ascat.runAscat(ascat.bc, gamma=1)
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}
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#Extract metrics from ASCAT profiles
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QC = ascat.metrics(ascat.bc,ascat.output)
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#Write out segmented regions (including regions with one copy of each allele)
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write.table(ascat.output[["segments"]], file=paste0("$prefix", ".segments.txt"), sep="\t", quote=F, row.names=F)
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#Write out CNVs in bed format
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cnvs=ascat.output[["segments"]][2:6]
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write.table(cnvs, file=paste0("$prefix",".cnvs.txt"), sep="\t", quote=F, row.names=F, col.names=T)
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#Write out purity and ploidy info
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summary <- tryCatch({
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matrix(c(ascat.output[["aberrantcellfraction"]], ascat.output[["ploidy"]]), ncol=2, byrow=TRUE)}, error = function(err) {
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# error handler picks up where error was generated
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print(paste("Could not find optimal solution: ",err))
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return(matrix(c(0,0),nrow=1,ncol=2,byrow = TRUE))
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}
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)
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colnames(summary) <- c("AberrantCellFraction","Ploidy")
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write.table(summary, file=paste0("$prefix",".purityploidy.txt"), sep="\t", quote=F, row.names=F, col.names=T)
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write.table(QC, file=paste0("$prefix", ".metrics.txt"), sep="\t", quote=F, row.names=F)
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# version export
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f <- file("versions.yml","w")
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alleleCounter_version = system(paste("alleleCounter --version"), intern = T)
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ascat_version = sessionInfo()\$otherPkgs\$ASCAT\$Version
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writeLines(paste0('"', "$task.process", '"', ":"), f)
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writeLines(paste(" alleleCounter:", alleleCounter_version), f)
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writeLines(paste(" ascat:", ascat_version), f)
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close(f)
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"""
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stub:
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def prefix = task.ext.prefix ?: "${meta.id}"
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"""
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echo stub > ${prefix}.cnvs.txt
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echo stub > ${prefix}.metrics.txt
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echo stub > ${prefix}.purityploidy.txt
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echo stub > ${prefix}.segments.txt
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echo stub > Tumour.ASCATprofile.png
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echo stub > Tumour.ASPCF.png
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echo stub > Before_correction_Tumour.germline.png
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echo stub > After_correction_GC_Tumour.germline.png
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echo stub > Tumour.rawprofile.png
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echo stub > Tumour.sunrise.png
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echo stub > Before_correction_Tumour.tumour.png
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echo stub > After_correction_GC_Tumour.tumour.png
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echo stub > Tumour_alleleFrequencies_chr21.txt
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echo stub > Tumour_alleleFrequencies_chr22.txt
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echo stub > Normal_alleleFrequencies_chr21.txt
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echo stub > Normal_alleleFrequencies_chr22.txt
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echo "${task.process}:" > versions.yml
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echo ' alleleCounter: 4.3.0' >> versions.yml
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echo ' ascat: 3.0.0' >> versions.yml
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"""
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}
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