243 lines
10 KiB
Scala
243 lines
10 KiB
Scala
/*
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* Copyright (c) 2011, The Broad Institute
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*
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* Permission is hereby granted, free of charge, to any person
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* obtaining a copy of this software and associated documentation
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* files (the "Software"), to deal in the Software without
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* restriction, including without limitation the rights to use,
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* copy, modify, merge, publish, distribute, sublicense, and/or sell
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* copies of the Software, and to permit persons to whom the
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* Software is furnished to do so, subject to the following
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* conditions:
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*
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* The above copyright notice and this permission notice shall be
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* included in all copies or substantial portions of the Software.
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
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* EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
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* OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
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* NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
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* HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
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* WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
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* FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
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* OTHER DEALINGS IN THE SOFTWARE.
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*/
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import org.broadinstitute.sting.queue.QScript
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import org.broadinstitute.sting.queue.extensions.gatk._
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import org.broadinstitute.sting.utils.interval.IntervalUtils
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class WholeGenomePipeline extends QScript {
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@Input(doc="Bam file list", shortName = "I", required=true)
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var bamList: File = _
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@Input(doc="Exclude intervals list", shortName = "XL", required=false)
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var excludeIntervals: List[File] = Nil
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@Argument(doc="path to tmp space for storing intermediate bam files", shortName="cleanerTmpDir", required=true)
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var cleanerTmpDir: String = _
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@Argument(doc="Flag for running the whole genome (wg) or chromosome 20 (chr20). The default is chr20.", shortName="runType", required=false)
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var runType = "chr20"
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@Argument(doc="Chunk size. Defaults to 3,000,000", shortName="chunk", required=false)
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var chunkSize = 3000000
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val resources = "/humgen/gsa-pipeline/resources/5777/b37/"
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val reference = resources + "human_g1k_v37.fasta"
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val dbsnp = resources + "dbsnp_132.b37.vcf"
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val indels = resources + "1000G_indels_for_realignment.b37.vcf"
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val omni = resources + "1000G_omni2.5.b37.sites.vcf"
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val hapmap = resources + "hapmap_3.3.b37.sites.vcf"
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trait CommandLineGATKArgs extends CommandLineGATK {
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this.reference_sequence = reference
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this.intervalsString = runIntervals
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this.memoryLimit = 2
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}
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case class Interval(chr: String, start: Long, stop: Long) {
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override def toString = "%s:%d-%d".format(chr, start, stop)
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}
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var runIntervals = List.empty[String]
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def script() {
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var intervals = Traversable.empty[Interval]
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runType = runType.toLowerCase
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if (runType == "wg") {
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val contigs = (1 to 22).map(_.toString) ++ List("X", "Y", "MT")
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val sizes = IntervalUtils.getContigSizes(reference)
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intervals = contigs.map(chr => new Interval(chr, 1, sizes.get(chr).longValue))
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runIntervals = Nil
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} else {
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val locs = Map(
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"cent1" -> new Interval("1", 121429168, 121529168),
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"cent16" -> new Interval("16", 40844464, 40944464),
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"chr20" -> new Interval("20", 1, 63025520),
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"chr20_100k" -> new Interval("20", 100001, 200000))
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locs.get(runType) match {
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case Some(range) =>
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intervals = List(range)
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runIntervals = List(range.toString)
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case None =>
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throw new RuntimeException("Invalid runType: " + runType + ". Must be one of: " + locs.keys.mkString(", ") + ", or wg")
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}
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}
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val project = Array(".bams.list", ".bam.list", ".list").foldLeft(bamList.getName)(_.stripSuffix(_))
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val projectBase = project + "." + runType
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var chunkVcfs = List.empty[File]
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for (interval <- intervals) {
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val chr = interval.chr
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val chrStart = interval.start
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val chrStop = interval.stop
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var start = chrStart
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var chunkNumber = 1
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while (start <= chrStop) {
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val stop = (start + chunkSize - 1) min chrStop
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val chunkBase: String = "chunks/" + project + "." + runType + "_chunk_" + chr + "_" + chunkNumber
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val tmpBase: String = cleanerTmpDir + "/" + chunkBase
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val chunkInterval = List("%s:%d-%d".format(chr, start, stop))
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val target = new RealignerTargetCreator with CommandLineGATKArgs
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target.input_file :+= bamList
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target.intervalsString = chunkInterval
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target.excludeIntervals = excludeIntervals
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target.mismatchFraction = 0.0
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target.rodBind :+= RodBind("dbsnp", "VCF", dbsnp)
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target.rodBind :+= RodBind("indels", "VCF", indels)
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target.out = tmpBase + ".target.intervals"
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target.jobOutputFile = chunkBase + ".target.intervals.out"
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target.isIntermediate = true
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add(target)
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val clean = new IndelRealigner with CommandLineGATKArgs
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clean.input_file :+= bamList
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clean.intervalsString = chunkInterval
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clean.excludeIntervals = excludeIntervals
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clean.targetIntervals = target.out
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clean.rodBind :+= RodBind("dbsnp", "VCF", dbsnp)
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clean.rodBind :+= RodBind("indels", "VCF", indels)
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clean.doNotUseSW = true
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clean.simplifyBAM = true
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clean.bam_compression = 1
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clean.out = tmpBase + ".cleaned.bam"
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clean.jobOutputFile = chunkBase + ".cleaned.bam.out"
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clean.isIntermediate = true
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add(clean)
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val call = new UnifiedGenotyper with CommandLineGATKArgs
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call.input_file :+= clean.out
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call.intervalsString = chunkInterval
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call.excludeIntervals = excludeIntervals
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call.rodBind :+= RodBind("dbsnp", "VCF", dbsnp)
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call.downsample_to_coverage = 50
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call.standard_min_confidence_threshold_for_calling = 4.0
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call.standard_min_confidence_threshold_for_emitting = 4.0
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call.baq = org.broadinstitute.sting.utils.baq.BAQ.CalculationMode.CALCULATE_AS_NECESSARY
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call.genotype_likelihoods_model = org.broadinstitute.sting.gatk.walkers.genotyper.GenotypeLikelihoodsCalculationModel.Model.BOTH
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call.GSA_PRODUCTION_ONLY = true
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call.out = chunkBase + ".vcf"
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call.jobOutputFile = call.out + ".out"
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add(call)
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chunkVcfs :+= call.out
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start += chunkSize
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chunkNumber += 1
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}
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}
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val combineChunks = new CombineVariants with CommandLineGATKArgs
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combineChunks.rodBind = chunkVcfs.zipWithIndex.map { case (vcf, index) => RodBind("input"+index, "VCF", vcf) }
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combineChunks.rod_priority_list = chunkVcfs.zipWithIndex.map { case (vcf, index) => "input"+index }.mkString(",")
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combineChunks.variantmergeoption = org.broadinstitute.sting.gatk.contexts.variantcontext.VariantContextUtils.VariantMergeType.UNION
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combineChunks.assumeIdenticalSamples = true
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combineChunks.out = projectBase + ".unfiltered.vcf"
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combineChunks.jobOutputFile = combineChunks.out + ".out"
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add(combineChunks)
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val selectSNPs = new SelectVariants with CommandLineGATKArgs
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selectSNPs.selectSNPs = true
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selectSNPs.rodBind :+= RodBind("variant", "VCF", combineChunks.out)
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selectSNPs.out = projectBase + ".snps.unrecalibrated.vcf"
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selectSNPs.jobOutputFile = selectSNPs.out + ".out"
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add(selectSNPs)
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val selectIndels = new SelectVariants with CommandLineGATKArgs
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selectIndels.selectIndels = true
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selectIndels.rodBind :+= RodBind("variant", "VCF", combineChunks.out)
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selectIndels.out = projectBase + ".indels.unfiltered.vcf"
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selectIndels.jobOutputFile = selectIndels.out + ".out"
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add(selectIndels)
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val filterIndels = new VariantFiltration with CommandLineGATKArgs
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filterIndels.variantVCF = selectIndels.out
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filterIndels.filterName = List("Indel_QUAL", "Indel_SB", "Indel_QD", "Indel_HRun", "Indel_HaplotypeScore")
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filterIndels.filterExpression = List("\"QUAL<30.0\"", "\"SB>-1.0\"", "\"QD<2.0\"", "\"HRun>15\"", "\"HaplotypeScore>20.0\"")
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filterIndels.out = projectBase + ".indels.filtered.vcf"
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filterIndels.jobOutputFile = filterIndels.out + ".out"
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add(filterIndels)
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val combineSNPsIndels = new CombineVariants with CommandLineGATKArgs
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combineSNPsIndels.rodBind :+= RodBind("indels", "VCF", selectIndels.out)
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combineSNPsIndels.rodBind :+= RodBind("all", "VCF", combineChunks.out)
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combineSNPsIndels.rod_priority_list = "indels,all"
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combineSNPsIndels.variantmergeoption = org.broadinstitute.sting.gatk.contexts.variantcontext.VariantContextUtils.VariantMergeType.UNION
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combineSNPsIndels.assumeIdenticalSamples = true
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combineSNPsIndels.out = projectBase + ".unrecalibrated.vcf"
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combineSNPsIndels.jobOutputFile = combineSNPsIndels.out + ".out"
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add(combineSNPsIndels)
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val vr = new VariantRecalibrator with CommandLineGATKArgs
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vr.rodBind :+= RodBind("input", "VCF", combineSNPsIndels.out)
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vr.rodBind :+= RodBind("hapmap", "VCF", hapmap, "known=false,training=true,truth=true,prior=15.0")
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vr.rodBind :+= RodBind("omni", "VCF", omni, "known=false,training=true,truth=false,prior=12.0")
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vr.rodBind :+= RodBind("dbsnp", "VCF", dbsnp, "known=true,training=false,truth=false,prior=8.0")
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vr.trustAllPolymorphic = true
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vr.use_annotation = List("QD", "HaplotypeScore", "HRun", "MQRankSum", "ReadPosRankSum")
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vr.TStranche = List(
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"100.0", "99.9", "99.5", "99.3",
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"99.0", "98.9", "98.8",
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"98.5", "98.4", "98.3", "98.2", "98.1",
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"98.0",
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"97.0",
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"95.0",
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"90.0")
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vr.tranches_file = projectBase + ".tranches"
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vr.recal_file = projectBase + ".recal"
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vr.jobOutputFile = vr.recal_file + ".out"
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add(vr)
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for (tranche <- vr.TStranche) {
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val ar = new ApplyRecalibration with CommandLineGATKArgs
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ar.rodBind :+= RodBind("input", "VCF", combineSNPsIndels.out)
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ar.tranches_file = vr.tranches_file
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ar.recal_file = vr.recal_file
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ar.ts_filter_level = tranche.toDouble
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ar.out = projectBase + ".recalibrated." + tranche + ".vcf"
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ar.jobOutputFile = ar.out + ".out"
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add(ar)
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val eval = new VariantEval with CommandLineGATKArgs
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eval.tranchesFile = vr.tranches_file
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eval.rodBind :+= RodBind("eval", "VCF", ar.out)
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eval.rodBind :+= RodBind("dbsnp", "VCF", dbsnp)
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eval.doNotUseAllStandardStratifications = true
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eval.doNotUseAllStandardModules = true
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eval.evalModule = List("SimpleMetricsByAC", "TiTvVariantEvaluator", "CountVariants")
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eval.stratificationModule = List("EvalRod", "CompRod", "Novelty", "Filter", "FunctionalClass", "Sample")
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eval.out = swapExt(ar.out, ".vcf", ".eval")
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eval.jobOutputFile = eval.out + ".out"
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add(eval)
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}
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}
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}
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