import org.broadinstitute.sting.queue.extensions.gatk._ import org.broadinstitute.sting.queue.QScript class pbCalling extends QScript { qscript => @Argument(shortName="gatk", doc="gatk jar file", required=true) var gatkJarFile: File = _ @Argument(shortName="outputDir", doc="output directory", required=true) var outputDir: String = "./" @Argument(shortName="dataset", doc="selects the datasets to run. If not provided, all datasets will be used", required=false) var datasets: List[String] = Nil class Target( val baseName: String, val reference: File, val dbsnpFile: String, val hapmapFile: String, val maskFile: String, val bamList: File, val goldStandard_VCF: File, val intervals: String, val titvTarget: Double, val isLowpass: Boolean, val isCCS: Boolean) { val name = qscript.outputDir + baseName val clusterFile = new File(name + ".clusters") val rawVCF = new File(name + ".raw.vcf") val filteredVCF = new File(name + ".filtered.vcf") val titvRecalibratedVCF = new File(name + ".titv.recalibrated.vcf") val titvTranchesFile = new File(name + ".titv.tranches") val recalibratedVCF = new File(name + ".ts.recalibrated.vcf") val tranchesFile = new File(name + ".ts.tranches") val cutVCF = new File(name + ".cut.vcf") val evalFile = new File(name + ".eval") val goldStandardName = qscript.outputDir + "goldStandard/" + baseName val goldStandardClusterFile = new File(goldStandardName + ".clusters") } val hg19 = new File("/seq/references/Homo_sapiens_assembly19/v1/Homo_sapiens_assembly19.fasta") val hg18 = new File("/seq/references/Homo_sapiens_assembly18/v0/Homo_sapiens_assembly18.fasta") val b36 = new File("/humgen/1kg/reference/human_b36_both.fasta") val b37 = new File("/humgen/1kg/reference/human_g1k_v37.fasta") val dbSNP_hg18 = "/humgen/gsa-hpprojects/GATK/data/Comparisons/Validated/dbSNP/dbsnp_130_hg18.rod" val dbSNP_b36 = "/humgen/gsa-hpprojects/GATK/data/Comparisons/Validated/dbSNP/dbsnp_130_b36.rod" val dbSNP_b37 = "/humgen/gsa-hpprojects/GATK/data/Comparisons/Validated/dbSNP/dbsnp_132_b37.leftAligned.vcf" val dbSNP_b37_129 = "/humgen/gsa-hpprojects/GATK/data/Comparisons/Validated/dbSNP/dbsnp_129_b37.rod" // Special case for NA12878 collections that can't use 132 because they are part of it. val hapmap_hg18 = "/humgen/gsa-hpprojects/GATK/data/Comparisons/Validated/HapMap/3.3/genotypes_r27_nr.hg18_fwd.vcf" val hapmap_b36 = "/humgen/gsa-hpprojects/GATK/data/Comparisons/Validated/HapMap/3.3/genotypes_r27_nr.b36_fwd.vcf" val hapmap_b37 = "/humgen/gsa-hpprojects/GATK/data/Comparisons/Validated/HapMap/3.3/genotypes_r27_nr.b37_fwd.vcf" val indelMask_b36 = "/humgen/1kg/processing/pipeline_test_bams/pilot1.dindel.mask.b36.bed" val indelMask_b37 = "/humgen/1kg/processing/pipeline_test_bams/pilot1.dindel.mask.b37.bed" // ToDos: // reduce the scope of the datasets so the script is more nimble // 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 // create gold standard BAQ'd bam files, no reason to always do it on the fly // Analysis to add at the end of the script: // auto generation of the cluster plots // 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 // produce Kiran's Venn plots based on comparison between new VCF and gold standard produced VCF val lowPass: Boolean = true val ccs: Boolean = true val targetDataSets: Map[String, Target] = Map( "HiSeq" -> new Target("NA12878.HiSeq", hg18, dbSNP_hg18, hapmap_hg18, "/humgen/gsa-hpprojects/dev/depristo/oneOffProjects/1000GenomesProcessingPaper/wgs.v13/HiSeq.WGS.cleaned.indels.10.mask", new File("/humgen/gsa-hpprojects/NA12878Collection/bams/NA12878.HiSeq.WGS.bwa.cleaned.recal.bam"), new File("/home/radon01/depristo/work/oneOffProjects/1000GenomesProcessingPaper/wgs.v13/HiSeq.WGS.cleaned.ug.snpfiltered.indelfiltered.vcf"), "/humgen/1kg/processing/pipeline_test_bams/whole_genome_chunked.hg18.intervals", 2.07, !lowPass, !ccs), "FIN" -> new Target("FIN", b37, dbSNP_b37, hapmap_b37, indelMask_b37, new File("/humgen/1kg/processing/pipeline_test_bams/FIN.79sample.Nov2010.chr20.bam"), new File("/humgen/gsa-hpprojects/dev/data/AugChr20Calls_v4_3state/ALL.august.v4.chr20.filtered.vcf"), // ** THIS GOLD STANDARD NEEDS TO BE CORRECTED ** "/humgen/1kg/processing/pipeline_test_bams/whole_genome_chunked.chr20.hg19.intervals", 2.3, lowPass, !ccs), "WEx" -> new Target("NA12878.WEx", hg18, dbSNP_hg18, hapmap_hg18, "/humgen/gsa-hpprojects/dev/depristo/oneOffProjects/1000GenomesProcessingPaper/wgs.v13/GA2.WEx.cleaned.indels.10.mask", new File("/humgen/gsa-hpprojects/NA12878Collection/bams/NA12878.WEx.cleaned.recal.bam"), new File("/home/radon01/depristo/work/oneOffProjects/1000GenomesProcessingPaper/wgs.v13/GA2.WEx.cleaned.ug.snpfiltered.indelfiltered.vcf"), "/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, !ccs), "TGPWExGdA" -> new Target("1000G.WEx.GdA", b37, dbSNP_b37, hapmap_b37, indelMask_b37, new File("/humgen/1kg/processing/pipeline_test_bams/Barcoded_1000G_WEx_Reduced_Plate_1.cleaned.list"), // BUGBUG: reduce from 60 to 20 people 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 ** "/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, !ccs), "LowPassN60" -> new Target("lowpass.N60", b36, dbSNP_b36, hapmap_b36, indelMask_b36, new File("/humgen/1kg/analysis/bamsForDataProcessingPapers/lowpass_b36/lowpass.chr20.cleaned.matefixed.bam"), // the bam list to call from new File("/home/radon01/depristo/work/oneOffProjects/VQSRCutByNRS/lowpass.N60.chr20.filtered.vcf"), // the gold standard VCF file to run through the VQSR "/humgen/1kg/processing/pipeline_test_bams/whole_genome_chunked.chr20.b36.intervals", 2.3, lowPass, !ccs), // chunked interval list to use with Queue's scatter/gather functionality "LowPassAugust" -> new Target("ALL.august.v4", b37, dbSNP_b37, hapmap_b37, indelMask_b37, // BUGBUG: kill this, it is too large new File("/humgen/1kg/processing/allPopulations_chr20_august_release.cleaned.merged.bams/ALL.cleaned.merged.list"), new File("/humgen/gsa-hpprojects/dev/data/AugChr20Calls_v4_3state/ALL.august.v4.chr20.filtered.vcf"), "/humgen/1kg/processing/pipeline_test_bams/whole_genome_chunked.chr20.hg19.intervals", 2.3, lowPass, !ccs), "LowPassEUR363Nov" -> new Target("EUR.nov2010", b37, dbSNP_b37, hapmap_b37, indelMask_b37, new File("/humgen/1kg/processing/pipeline_test_bams/EUR.363sample.Nov2010.chr20.bam"), new File("/humgen/gsa-hpprojects/dev/data/AugChr20Calls_v4_3state/ALL.august.v4.chr20.filtered.vcf"), // ** THIS GOLD STANDARD NEEDS TO BE CORRECTED ** "/humgen/1kg/processing/pipeline_test_bams/whole_genome_chunked.chr20.hg19.intervals", 2.3, lowPass, !ccs), "WExTrio" -> new Target("NA12878Trio.WEx", b37, dbSNP_b37_129, hapmap_b37, indelMask_b37, new File("/humgen/gsa-hpprojects/NA12878Collection/bams/CEUTrio.HiSeq.WEx.bwa.cleaned.recal.bam"), new File("/humgen/gsa-scr1/carneiro/prj/trio/snps/NA12878Trio.WEx.filtered.vcf"), "/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, !ccs), "pacbio" -> new Target("pacbio", b37, dbSNP_b37_129, hapmap_b37, indelMask_b37, new File("/humgen/gsa-scr1/carneiro/prj/pacbio/data/pacbio.recal.bam"), new File("/humgen/gsa-scr1/carneiro/prj/pacbio/analisys/snps/pacbio.filtered.vcf"), "/humgen/gsa-scr1/carneiro/prj/pacbio/data/pacbio.hg19.intervals", 1.8, !lowPass, !ccs), "pb200" -> new Target("pb200", b37, dbSNP_b37_129, hapmap_b37, indelMask_b37, new File("/humgen/gsa-scr1/carneiro/prj/pacbio/data/pb200.recal.bam"), new File("/humgen/gsa-scr1/carneiro/prj/pacbio/analisys/snps/pb200.filtered.vcf"), "/humgen/gsa-scr1/carneiro/prj/pacbio/data/pb200.hg19.intervals", 1.8, !lowPass, !ccs), "pb2k" -> new Target("pb2k", b37, dbSNP_b37_129, hapmap_b37, indelMask_b37, new File("/humgen/gsa-scr1/carneiro/prj/pacbio/data/pb2k.recal.bam"), new File("/humgen/gsa-scr1/carneiro/prj/pacbio/analisys/snps/pb2k.filtered.vcf"), "/humgen/gsa-scr1/carneiro/prj/pacbio/data/pb2k.hg19.intervals", 1.8, !lowPass, !ccs), "cc200" -> new Target("cc200", b37, dbSNP_b37_129, hapmap_b37, indelMask_b37, new File("/humgen/gsa-scr1/carneiro/prj/pacbio/data/cc200.recal.bam"), new File("/humgen/gsa-scr1/carneiro/prj/pacbio/analisys/snps/cc200.filtered.vcf"), "/humgen/gsa-scr1/carneiro/prj/pacbio/data/cc200.hg19.intervals", 1.8, !lowPass, ccs), "cc2k" -> new Target("cc2k", b37, dbSNP_b37_129, hapmap_b37, indelMask_b37, new File("/humgen/gsa-scr1/carneiro/prj/pacbio/data/cc2k.recal.bam"), new File("/humgen/gsa-scr1/carneiro/prj/pacbio/analisys/snps/cc2k.filtered.vcf"), "/humgen/gsa-scr1/carneiro/prj/pacbio/data/cc2k.hg19.intervals", 1.8, !lowPass, ccs) ) def script = { // Selects the datasets in the -dataset argument and adds them to targets. var targets: List[Target] = List() if (!datasets.isEmpty) for (ds <- datasets) targets ::= targetDataSets(ds) // Could check if ds was mispelled, but this way an exception will be thrown, maybe it's better this way? else // If -dataset is not specified, all datasets are used. for (targetDS <- targetDataSets.valuesIterator) // for Scala 2.7 or older, use targetDataSets.values targets ::= targetDS val goldStandard = true for (target <- targets) { add(new UnifiedGenotyper(target)) add(new VariantFiltration(target)) add(new VQSR(target, !goldStandard)) add(new applyVQSR(target, !goldStandard)) add(new VariantCut(target)) add(new VariantEvaluation(target)) } } def bai(bam: File) = new File(bam + ".bai") val FiltersToIgnore = List("DPFilter", "ABFilter", "ESPStandard", "QualByDepth", "StrandBias", "HomopolymerRun") // 1.) Call SNPs with UG class UnifiedGenotyper(t: Target) extends org.broadinstitute.sting.queue.extensions.gatk.UnifiedGenotyper { this.jarFile = gatkJarFile this.reference_sequence = t.reference this.intervalsString ++= List(t.intervals) this.scatterCount = 63 // the smallest interval list has 63 intervals, one for each Mb on chr20 this.dcov = if ( t.isLowpass ) { 50 } else { 250 } this.stand_call_conf = if ( t.isLowpass ) { 4.0 } else { 30.0 } this.stand_emit_conf = if ( t.isLowpass ) { 4.0 } else { 30.0 } this.input_file :+= t.bamList this.out = t.rawVCF this.baq = org.broadinstitute.sting.utils.baq.BAQ.CalculationMode.CALCULATE_AS_NECESSARY this.analysisName = t.name + "_UG" if (t.dbsnpFile.endsWith(".rod")) this.DBSNP = new File(t.dbsnpFile) else if (t.dbsnpFile.endsWith(".vcf")) this.rodBind :+= RodBind("dbsnp", "VCF", t.dbsnpFile) // Ridiculous workaround to get pacbio data to run.. never commit this! this.deletions = 0.5 this.mbq = 10 } // 2.) Filter SNPs class VariantFiltration(t: Target) extends org.broadinstitute.sting.queue.extensions.gatk.VariantFiltration { this.jarFile = gatkJarFile this.reference_sequence = t.reference this.intervalsString ++= List(t.intervals) this.scatterCount = 10 this.variantVCF = t.rawVCF this.out = t.filteredVCF this.filterName ++= List("HARD_TO_VALIDATE") this.filterExpression ++= List("\"MQ0 >= 4 && (MQ0 / (1.0 * DP)) > 0.1\"") this.analysisName = t.name + "_VF" } class VQSR(t: Target, goldStandard: Boolean) extends VariantRecalibrator { this.memoryLimit = 6 this.intervalsString ++= List(t.intervals) this.rodBind :+= RodBind("input", "VCF", if ( goldStandard ) { t.goldStandard_VCF } else { t.filteredVCF } ) this.rodBind :+= RodBind("hapmap", "VCF", t.hapmapFile) if( t.hapmapFile.contains("b37") ) this.rodBind :+= RodBind("1kg", "VCF", omni_b37) else if( t.hapmapFile.contains("b36") ) this.rodBind :+= RodBind("1kg", "VCF", omni_b36) if (t.dbsnpFile.endsWith(".rod")) this.DBSNP = new File(t.dbsnpFile) else if (t.dbsnpFile.endsWith(".vcf")) this.rodBind :+= RodBind("dbsnp", "VCF", t.dbsnpFile) this.use_annotation ++= List("QD", "SB", "HaplotypeScore", "HRun") this.tranches_file = if ( goldStandard ) { t.goldStandardTranchesFile } else { t.tranchesFile } this.recal_file = if ( goldStandard ) { t.goldStandardRecalFile } else { t.recalFile } this.allPoly = true this.tranche ++= List("0.1", "0.5", "0.7", "1.0", "1.1", "1.2", "1.5", "1.6", "1.7", "1.8", "1.9", "2.0", "2.1", "2.2", "2.5","3.0", "5.0", "10.0") } class applyVQSR (t: Target, goldStandard: Boolean) extends ApplyRecalibration { this.memoryLimit = 4 this.intervalsString ++= List(t.intervals) this.rodBind :+= RodBind("input", "VCF", if ( goldStandard ) { t.goldStandard_VCF } else { t.filteredVCF } ) this.tranches_file = if ( goldStandard ) { t.goldStandardTranchesFile } else { t.tranchesFile} this.recal_file = if ( goldStandard ) { t.goldStandardRecalFile } else { t.recalFile } this.fdr_filter_level = 2.0 this.out = t.recalibratedVCF } // 5.) Variant Cut filter out the variants marked by recalibration to the 99% tranche class VariantCut(t: Target) extends org.broadinstitute.sting.queue.extensions.gatk.ApplyVariantCuts { this.jarFile = gatkJarFile this.reference_sequence = t.reference this.rodBind :+= RodBind("input", "VCF", t.recalibratedVCF ) this.analysisName = t.name + "_VC" this.intervalsString ++= List(t.intervals) this.out = t.cutVCF this.tranchesFile = t.tranchesFile this.fdr_filter_level = 1.0 if (t.dbsnpFile.endsWith(".rod")) this.DBSNP = new File(t.dbsnpFile) else if (t.dbsnpFile.endsWith(".vcf")) this.rodBind :+= RodBind("dbsnp", "VCF", t.dbsnpFile) } // 6.) Variant Evaluation based on the sensitivity recalibrated vcf class VariantEvaluation(t: Target) extends org.broadinstitute.sting.queue.extensions.gatk.VariantEval { this.jarFile = gatkJarFile val name: String = t.name this.reference_sequence = t.reference this.rodBind :+= RodBind("comp", "VCF", t.hapmapFile) this.rodBind :+= RodBind("eval", "VCF", t.cutVCF) this.analysisName = name + "_VE" this.intervalsString ++= List(t.intervals) this.EV ++= List("GenotypeConcordance") this.out = t.evalFile // Ridiculous workaround to get pacbio data to run.. never commit this! this.sample ++= List("NA12878") } }