172 lines
11 KiB
Scala
Executable File
172 lines
11 KiB
Scala
Executable File
import org.broadinstitute.sting.queue.extensions.picard.PicardBamJarFunction
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import org.broadinstitute.sting.queue.extensions.gatk._
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import org.broadinstitute.sting.queue.extensions.samtools.SamtoolsIndexFunction
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import org.broadinstitute.sting.queue.QScript
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import org.apache.commons.io.FilenameUtils;
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class DistributedGATKPerformance extends QScript {
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qscript =>
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@Argument(shortName="gatk", doc="gatk jar file", required=true)
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var gatkJarFile: File = _
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@Argument(shortName="outputDir", doc="output directory", required=false)
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var outputDir: String = ""
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@Argument(shortName="dataset", doc="selects the datasets to run. If not provided, all datasets will be used", required=false)
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var datasets: List[String] = Nil
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@Argument(shortName="long", doc="runs long calculations", required=false)
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var long: Boolean = false
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//@Argument(shortName="noBAQ", doc="turns off BAQ calculation", required=false)
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var noBAQ: Boolean = false
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trait UNIVERSAL_GATK_ARGS extends CommandLineGATK { logging_level = "INFO"; jarFile = gatkJarFile; memoryLimit = Some(2); }
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class Target(
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val baseName: String,
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val reference: File,
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val dbsnpFile: String,
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val hapmapFile: String,
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val maskFile: String,
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val bamList: File,
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val goldStandard_VCF: File,
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val intervals: String,
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val titvTarget: Double,
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val isLowpass: Boolean) {
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val name = qscript.outputDir + baseName
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val clusterFile = new File(name + ".clusters")
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def rawVCF(part: String) = new File(name + "." + part + ".raw.vcf")
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val filteredVCF = new File(name + ".filtered.vcf")
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val titvRecalibratedVCF = new File(name + ".titv.recalibrated.vcf")
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val tsRecalibratedVCF = new File(name + ".ts.recalibrated.vcf")
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val goldStandardName = qscript.outputDir + "goldStandard/" + baseName
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val goldStandardClusterFile = new File(goldStandardName + ".clusters")
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}
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val hg18 = new File("/seq/references/Homo_sapiens_assembly18/v0/Homo_sapiens_assembly18.fasta")
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val b36 = new File("/humgen/1kg/reference/human_b36_both.fasta")
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val b37 = new File("/humgen/1kg/reference/human_g1k_v37.fasta")
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val dbSNP_hg18 = "/humgen/gsa-hpprojects/GATK/data/Comparisons/Validated/dbSNP/dbsnp_130_hg18.rod"
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val dbSNP_b36 = "/humgen/gsa-hpprojects/GATK/data/Comparisons/Validated/dbSNP/dbsnp_130_b36.rod"
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val dbSNP_b37 = "/humgen/gsa-hpprojects/GATK/data/Comparisons/Validated/dbSNP/dbsnp_132_b37.leftAligned.vcf"
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val hapmap_hg18 = "/humgen/gsa-hpprojects/GATK/data/Comparisons/Validated/HapMap/3.3/sites_r27_nr.hg18_fwd.vcf"
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val hapmap_b36 = "/humgen/gsa-hpprojects/GATK/data/Comparisons/Validated/HapMap/3.3/sites_r27_nr.b36_fwd.vcf"
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val hapmap_b37 = "/humgen/gsa-hpprojects/GATK/data/Comparisons/Validated/HapMap/3.3/sites_r27_nr.b37_fwd.vcf"
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val indelMask_b36 = "/humgen/1kg/processing/pipeline_test_bams/pilot1.dindel.mask.b36.bed"
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val indelMask_b37 = "/humgen/1kg/processing/pipeline_test_bams/pilot1.dindel.mask.b37.bed"
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// ToDos:
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// reduce the scope of the datasets so the script is more nimble
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// figure out how to give names to all the Queue-LSF logs (other than Q-1931@node1434-24.out) so that it is easier to find logs for certain steps
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// create gold standard BAQ'd bam files, no reason to always do it on the fly
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// Analysis to add at the end of the script:
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// auto generation of the cluster plots
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// spike in NA12878 to the exomes and to the lowpass, analysis of how much of her variants are being recovered compared to single sample exome or HiSeq calls
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// produce Kiran's Venn plots based on comparison between new VCF and gold standard produced VCF
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val lowPass: Boolean = true
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val CHROMOSOME: String = "chr1"
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val targetDataSets: Map[String, Target] = Map(
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"HiSeq" -> new Target("NA12878.HiSeq", hg18, dbSNP_hg18, hapmap_hg18,
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"/humgen/gsa-hpprojects/dev/depristo/oneOffProjects/1000GenomesProcessingPaper/wgs.v13/HiSeq.WGS.cleaned.indels.10.mask",
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new File("/humgen/gsa-hpprojects/NA12878Collection/bams/NA12878.HiSeq.WGS.bwa.cleaned.recal.bam"),
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new File("/home/radon01/depristo/work/oneOffProjects/1000GenomesProcessingPaper/wgs.v13/HiSeq.WGS.cleaned.ug.snpfiltered.indelfiltered.vcf"),
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"/humgen/gsa-hpprojects/dev/depristo/oneOffProjects/distributedGATK/whole_genome_chunked.hg18.intervals", 2.07, !lowPass),
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"FIN" -> new Target("FIN", b37, dbSNP_b37, hapmap_b37, indelMask_b37,
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new File("/humgen/1kg/processing/pipeline_test_bams/FIN.79sample.Nov2010.chr20.bam"),
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new File("/humgen/gsa-hpprojects/dev/data/AugChr20Calls_v4_3state/ALL.august.v4.chr20.filtered.vcf"), // ** THIS GOLD STANDARD NEEDS TO BE CORRECTED **
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"/humgen/1kg/processing/pipeline_test_bams/whole_genome_chunked.chr20.hg19.intervals", 2.3, lowPass),
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"WEx" -> new Target("NA12878.WEx", hg18, dbSNP_hg18, hapmap_hg18,
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"/humgen/gsa-hpprojects/dev/depristo/oneOffProjects/1000GenomesProcessingPaper/wgs.v13/GA2.WEx.cleaned.indels.10.mask",
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new File("/humgen/gsa-hpprojects/NA12878Collection/bams/NA12878.WEx.cleaned.recal.bam"),
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new File("/home/radon01/depristo/work/oneOffProjects/1000GenomesProcessingPaper/wgs.v13/GA2.WEx.cleaned.ug.snpfiltered.indelfiltered.vcf"),
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"/seq/references/HybSelOligos/whole_exome_agilent_1.1_refseq_plus_3_boosters/whole_exome_agilent_1.1_refseq_plus_3_boosters.targets.interval_list", 2.6, !lowPass),
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"TGPWExGdA" -> new Target("1000G.WEx.GdA", b37, dbSNP_b37, hapmap_b37, indelMask_b37,
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new File("/humgen/1kg/processing/pipeline_test_bams/Barcoded_1000G_WEx_Reduced_Plate_1.cleaned.list"), // BUGBUG: reduce from 60 to 20 people
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new File("/humgen/gsa-scr1/delangel/NewUG/calls/AugustRelease.filtered_Q50_QD5.0_SB0.0.allSamples.SNPs_hg19.WEx_UG_newUG_MQC.vcf"), // ** THIS GOLD STANDARD NEEDS TO BE CORRECTED **
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"/seq/references/HybSelOligos/whole_exome_agilent_1.1_refseq_plus_3_boosters/whole_exome_agilent_1.1_refseq_plus_3_boosters.Homo_sapiens_assembly19.targets.interval_list", 2.6, !lowPass),
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"LowPassN60" -> new Target("lowpass.N60", b36, dbSNP_b36, hapmap_b36, indelMask_b36,
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new File("/humgen/1kg/analysis/bamsForDataProcessingPapers/lowpass_b36/lowpass.chr20.cleaned.matefixed.bam"), // the bam list to call from
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new File("/home/radon01/depristo/work/oneOffProjects/VQSRCutByNRS/lowpass.N60.chr20.filtered.vcf"), // the gold standard VCF file to run through the VQSR
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"/humgen/1kg/processing/pipeline_test_bams/whole_genome_chunked.chr20.b36.intervals", 2.3, lowPass), // chunked interval list to use with Queue's scatter/gather functionality
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"LowPassAugust" -> new Target("ALL.august.v4", b37, dbSNP_b37, hapmap_b37, indelMask_b37, // BUGBUG: kill this, it is too large
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new File("/humgen/1kg/processing/allPopulations_chr20_august_release.cleaned.merged.bams/ALL.cleaned.merged.list"),
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new File("/humgen/gsa-hpprojects/dev/data/AugChr20Calls_v4_3state/ALL.august.v4.chr20.filtered.vcf"),
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"/humgen/1kg/processing/pipeline_test_bams/whole_genome_chunked.chr20.hg19.intervals", 2.3, lowPass),
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"LowPassEUR363Nov" -> new Target("EUR.nov2010", b37, dbSNP_b37, hapmap_b37, indelMask_b37,
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new File("/humgen/1kg/processing/pipeline_test_bams/EUR.363sample.Nov2010.chr20.bam"),
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new File("/humgen/gsa-hpprojects/dev/data/AugChr20Calls_v4_3state/ALL.august.v4.chr20.filtered.vcf"), // ** THIS GOLD STANDARD NEEDS TO BE CORRECTED **
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"/humgen/1kg/processing/pipeline_test_bams/whole_genome_chunked.chr20.hg19.intervals", 2.3, lowPass),
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"WExTrio" -> new Target("NA12878Trio.WEx", b37, dbSNP_b37, hapmap_b37, indelMask_b37,
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new File("/humgen/gsa-scr1/carneiro/prj/trio/NA12878Trio.WEx.hg19.bam"),
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new File("/humgen/gsa-scr1/delangel/NewUG/calls/AugustRelease.filtered_Q50_QD5.0_SB0.0.allSamples.SNPs_hg19.WEx_UG_newUG_MQC.vcf"), // ** THIS GOLD STANDARD NEEDS TO BE CORRECTED **
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"/seq/references/HybSelOligos/whole_exome_agilent_1.1_refseq_plus_3_boosters/whole_exome_agilent_1.1_refseq_plus_3_boosters.Homo_sapiens_assembly19.targets.interval_list", 2.6, !lowPass)
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)
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def script = {
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// Selects the datasets in the -dataset argument and adds them to targets.
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var targets: List[Target] = List()
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if (!datasets.isEmpty)
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for (ds <- datasets)
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targets ::= targetDataSets(ds) // Could check if ds was mispelled, but this way an exception will be thrown, maybe it's better this way?
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else // If -dataset is not specified, all datasets are used.
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for (targetDS <- targetDataSets.valuesIterator) // for Scala 2.7 or older, use targetDataSets.values
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targets ::= targetDS
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val nWays = if (long) List(1, 2, 4) else List(8, 16, 32, 64, 96)
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//val nWays = List(2)
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for (target <- targets) {
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for ( scatterP <- List(true, false) )
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for (nWaysParallel <- nWays) {
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val aname = "ptype_%s.nways_%d".format(if ( scatterP ) "sg" else "dist", nWaysParallel)
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def addUG(ug: UnifiedGenotyper) = {
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if ( ! long )
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ug.jobLimitSeconds = Some(60 * 60 * 4)
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add(ug);
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}
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// add scatter/gather or distributed parallelism
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if ( scatterP ) {
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var ug: UnifiedGenotyper = new UnifiedGenotyper(target, aname)
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ug.scatterCount = nWaysParallel
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ug.intervalsString ++= List(target.intervals)
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addUG(ug)
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} else {
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for ( part <- 1 to nWaysParallel) {
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var ug: UnifiedGenotyper = new UnifiedGenotyper(target, aname + ".part" + part)
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ug.intervalsString ++= List(CHROMOSOME)
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ug.processingTracker = new File(target.name + "." + aname + ".distributed.txt")
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if ( part == 1 )
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ug.performanceLog = new File("%s.%s.pf.log".format(target.name, aname))
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addUG(ug)
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}
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}
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}
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}
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}
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// 1.) Call SNPs with UG
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class UnifiedGenotyper(t: Target, aname: String) extends org.broadinstitute.sting.queue.extensions.gatk.UnifiedGenotyper with UNIVERSAL_GATK_ARGS {
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this.reference_sequence = t.reference
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this.dcov = Some( if ( t.isLowpass ) { 50 } else { 250 } )
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this.stand_call_conf = Some( if ( t.isLowpass ) { 4.0 } else { 30.0 } )
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this.stand_emit_conf = Some( if ( t.isLowpass ) { 4.0 } else { 30.0 } )
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this.input_file :+= t.bamList
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this.out = t.rawVCF(aname)
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this.baq = Some( if (noBAQ) {org.broadinstitute.sting.utils.baq.BAQ.CalculationMode.OFF} else {org.broadinstitute.sting.utils.baq.BAQ.CalculationMode.RECALCULATE})
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this.analysisName = t.name + "_UG." + aname
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if (t.dbsnpFile.endsWith(".rod"))
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this.DBSNP = new File(t.dbsnpFile)
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else if (t.dbsnpFile.endsWith(".vcf"))
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this.rodBind :+= RodBind("dbsnp", "VCF", t.dbsnpFile)
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}
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}
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