364 lines
18 KiB
Scala
Executable File
364 lines
18 KiB
Scala
Executable File
import org.broadinstitute.sting.queue.extensions.picard.PicardBamJarFunction
|
|
import org.broadinstitute.sting.queue.extensions.gatk._
|
|
import org.broadinstitute.sting.queue.extensions.samtools.SamtoolsIndexFunction
|
|
import org.broadinstitute.sting.queue.QScript
|
|
import org.apache.commons.io.FilenameUtils;
|
|
|
|
class VQSR_parameterSearch extends QScript {
|
|
qscript =>
|
|
|
|
@Argument(shortName="gatk", doc="gatk jar file", required=true)
|
|
var gatkJarFile: File = _
|
|
|
|
@Argument(shortName="experiment", doc="experiment number", required=true)
|
|
var experiment: String = "0000"
|
|
|
|
@Argument(shortName="outputDir", doc="output directory", required=true)
|
|
var outputDir: String = "./"
|
|
|
|
@Argument(shortName="skipCalling", doc="If true, skip the calling part of the pipeline and only run VQSR on preset, gold standard VCF files", required=false)
|
|
var skipCalling: Boolean = false
|
|
|
|
trait UNIVERSAL_GATK_ARGS extends CommandLineGATK { logging_level = "INFO"; jarFile = gatkJarFile; memoryLimit = Some(2); }
|
|
|
|
class Target(val baseName: String, val reference: File, val rodName: String, val bamList: File, val goldStandard_VCF: File, val intervals: String, val titvTarget: Double, val isLowpass: Boolean) {
|
|
def name = qscript.outputDir + baseName
|
|
def clusterFile = new File(name + ".clusters")
|
|
def rawVCF = new File(name + ".raw.vcf")
|
|
def filteredVCF = new File(name + ".filtered.vcf")
|
|
def goldStandardName = qscript.outputDir + "goldStandard/" + baseName
|
|
var goldStandardClusterFile: File = new File("")
|
|
var gaussian: Int = 1
|
|
var shrinkage: Double = 1.0
|
|
var dirichlet: Double = 1.0
|
|
var backoff: Double = 1.0
|
|
var qualCutoff: Int = 1
|
|
var std: Double = 1.0
|
|
var useQD: Int = 1
|
|
var useSB: Int = 1
|
|
var useHS: Int = 1
|
|
var useHRUN: Int = 1
|
|
var useMQRST: Int = 1
|
|
var useBQRST: Int = 1
|
|
var useGC: Int = 1
|
|
var useMQ: Int = 1
|
|
var useSumGL: Int = 1
|
|
var trainOmni: Int = 1
|
|
}
|
|
|
|
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")
|
|
|
|
// 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
|
|
|
|
// Define the target datasets here
|
|
def lowPass = true
|
|
val HiSeq = new Target("NA12878.HiSeq", hg18, "hg18", // BUGBUG: cut down to chr1
|
|
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)
|
|
val WEx = new Target("NA12878.WEx", hg18, "hg18",
|
|
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)
|
|
val LowPassN60 = new Target("lowpass.N60", b36, "b36", // which reference the data is aligned to
|
|
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) // chunked interval list to use with Queue's scatter/gather functionality
|
|
val LowPassAugust = new Target("ALL.august.v4", b37, "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)
|
|
val LowPassEUR363Nov = new Target("EUR.nov2010", b37, "b37",
|
|
new File("/humgen/1kg/processing/pipeline_test_bams/EUR.363sample.Nov2010.chr20.bam"),
|
|
new File("/humgen/gsa-hpprojects/dev/rpoplin/haplotypeScore/sting_dev_oldQD_hs10/logs/EUR.nov.filtered.vcf"), // ** THIS GOLD STANDARD NEEDS TO BE CORRECTED **
|
|
"/humgen/1kg/processing/pipeline_test_bams/whole_genome_chunked.chr20.hg19.intervals", 2.3, lowPass)
|
|
val LowPassFIN79Nov = new Target("FIN.nov2010", b37, "b37",
|
|
new File("/humgen/1kg/processing/pipeline_test_bams/FIN.79sample.Nov2010.chr20.bam"),
|
|
new File("/broad/shptmp/rpoplin/pipeline_newHS7/FIN.nov2010.filtered.vcf"), // ** THIS GOLD STANDARD NEEDS TO BE CORRECTED **
|
|
"/humgen/1kg/processing/pipeline_test_bams/whole_genome_chunked.chr20.hg19.intervals", 2.3, lowPass)
|
|
val TGPWExGdA = new Target("1000G.WEx.GdA", b37, "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)
|
|
|
|
//val targets = List(HiSeq, WEx, LowPassN60, LowPassAugust, LowPassEUR363Nov, LowPassFIN79Nov, TGPWExGdA)
|
|
val targets = List(LowPassEUR363Nov)
|
|
def script = {
|
|
def goldStandard = true
|
|
|
|
var gaussianList = List(6)
|
|
var shrinkageList = List(0.0001)
|
|
var dirichletList = List(1000.0)
|
|
var backoffList = List(1.3)
|
|
var qualCutoffList = List(100)
|
|
var stdList = List(4.5)
|
|
var useQDList = List(1)
|
|
var useSBList = List(1)
|
|
var useHSList = List(1)
|
|
var useHRUNList = List(1)
|
|
var useMQRSTList = List(0)
|
|
var useBQRSTList = List(0)
|
|
var useGCList = List(0)
|
|
var useMQList = List(0)
|
|
var useSumGLList = List(0)
|
|
var trainOmniList = List(1)
|
|
|
|
if(experiment == "0000") {
|
|
gaussianList = List(6,16)
|
|
trainOmniList = List(0,1)
|
|
useMQRSTList = List(0,1)
|
|
}
|
|
if(experiment == "0001") {
|
|
gaussianList = List(6, 16)
|
|
shrinkageList = List(0.0001, 0.01)
|
|
dirichletList = List(0.001, 1000.0)
|
|
backoffList = List(0.7, 1.0, 1.3)
|
|
useQDList = List(0,1)
|
|
useSBList = List(0,1)
|
|
useHSList = List(0,1)
|
|
useHRUNList = List(0,1)
|
|
useMQRSTList = List(0,1)
|
|
useBQRSTList = List(0,1)
|
|
useSumGLList = List(0,1)
|
|
trainOmniList = List(0,1)
|
|
}
|
|
if(experiment == "0002") {
|
|
gaussianList = List(2, 10, 50)
|
|
stdList = List(2.0, 4.5, 8.5)
|
|
dirichletList = List(0.0001, 0.01)
|
|
backoffList = List(0.5, 0.6, 0.9)
|
|
useQDList = List(1)
|
|
useSBList = List(0,1)
|
|
useHSList = List(0,1)
|
|
useHRUNList = List(0)
|
|
useMQRSTList = List(0,1)
|
|
useBQRSTList = List(0)
|
|
useSumGLList = List(0,1)
|
|
useGCList = List(0,1)
|
|
useMQList = List(0,1)
|
|
trainOmniList = List(0,1)
|
|
}
|
|
if(experiment == "0003") {
|
|
qualCutoffList = List(5, 40, 100, 400)
|
|
shrinkageList = List(0.0001, 0.001, 0.1)
|
|
dirichletList = List(0.0001, 0.001, 0.01)
|
|
useQDList = List(1)
|
|
useSBList = List(0,1)
|
|
useHSList = List(1)
|
|
useHRUNList = List(0)
|
|
useMQRSTList = List(0,1)
|
|
useBQRSTList = List(0,1)
|
|
useGCList = List(0,1)
|
|
useMQList = List(0,1)
|
|
useSumGLList = List(0,1)
|
|
trainOmniList = List(0,1)
|
|
}
|
|
if(experiment == "0004") {
|
|
gaussianList = List(5, 25)
|
|
shrinkageList = List(0.01, 1.0, 100.0)
|
|
dirichletList = List(0.001, 10.0, 1000.0)
|
|
backoffList = List(0.6, 1.0, 1.4)
|
|
useQDList = List(1)
|
|
useSBList = List(1)
|
|
useHSList = List(0,1)
|
|
useHRUNList = List(0,1)
|
|
useMQRSTList = List(0,1)
|
|
useBQRSTList = List(0,1)
|
|
useGCList = List(0,1)
|
|
useMQList = List(0,1)
|
|
}
|
|
if(experiment == "0005") {
|
|
gaussianList = List(4,50,100)
|
|
shrinkageList = List(0.0001, 10.0)
|
|
dirichletList = List(0.0001, 0.001)
|
|
backoffList = List(0.2, 0.3, 0.6)
|
|
stdList = List(0.5, 1.0, 10.0)
|
|
useQDList = List(1)
|
|
useSBList = List(1)
|
|
useHSList = List(1)
|
|
useHRUNList = List(0,1)
|
|
useMQRSTList = List(0,1)
|
|
useBQRSTList = List(0,1)
|
|
useGCList = List(0,1)
|
|
useMQList = List(0)
|
|
trainOmniList = List(0,1)
|
|
}
|
|
|
|
|
|
|
|
for (target <- targets) {
|
|
|
|
|
|
|
|
for(gaussian: Int <- gaussianList) {
|
|
for(shrinkage: Double <- shrinkageList) {
|
|
for(dirichlet: Double <- dirichletList) {
|
|
for(backoff: Double <- backoffList) {
|
|
for(qualCutoff: Int <- qualCutoffList) {
|
|
for(std: Double <- stdList) {
|
|
for(useQD: Int <- useQDList ) {
|
|
for(useSB: Int <- useSBList ) {
|
|
for(useHS: Int <- useHSList ) {
|
|
for(useHRUN: Int <- useHRUNList ) {
|
|
for(useMQRST: Int <- useMQRSTList ) {
|
|
for(useBQRST: Int <- useBQRSTList ) {
|
|
for(useGC: Int <- useGCList ) {
|
|
for(useMQ: Int <- useMQList ) {
|
|
for(useSumGL: Int <- useSumGLList ) {
|
|
for(trainOmni: Int <- trainOmniList) {
|
|
|
|
target.gaussian = gaussian
|
|
target.shrinkage = shrinkage
|
|
target.dirichlet = dirichlet
|
|
target.backoff = backoff
|
|
target.qualCutoff = qualCutoff
|
|
target.std = std
|
|
target.useQD = useQD
|
|
target.useSB = useSB
|
|
target.useHS = useHS
|
|
target.useHRUN = useHRUN
|
|
target.useMQRST = useMQRST
|
|
target.useBQRST = useBQRST
|
|
target.useGC = useGC
|
|
target.useMQ = useMQ
|
|
target.useSumGL = useSumGL
|
|
target.trainOmni = trainOmni
|
|
val clustersName: String = "%s_%d_%.4f_%.4f_%.1f_%d_%.1f_%d%d%d%d%d%d%d%d%d_%d.clusters".format(target.name, target.gaussian, target.shrinkage, target.dirichlet, target.backoff, target.qualCutoff, target.std, target.useQD, target.useSB, target.useHS, target.useHRUN, target.useMQRST, target.useBQRST, target.useGC, target.useMQ, target.useSumGL, target.trainOmni)
|
|
target.goldStandardClusterFile = new File(clustersName)
|
|
add(new GenerateVariantClusters(target, goldStandard))
|
|
add(new VariantRecalibratorTiTv(target, goldStandard))
|
|
add(new VariantRecalibratorNRS(target, goldStandard))
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
def bai(bam: File) = new File(bam + ".bai")
|
|
|
|
val FiltersToIgnore = List("DPFilter", "ABFilter", "ESPStandard", "QualByDepth", "StrandBias", "HomopolymerRun")
|
|
|
|
// 3.) VQSR part1 Generate Gaussian clusters based on truth sites
|
|
class GenerateVariantClusters(t: Target, goldStandard: Boolean) extends org.broadinstitute.sting.queue.extensions.gatk.GenerateVariantClusters with UNIVERSAL_GATK_ARGS {
|
|
val name: String = if ( goldStandard ) { t.goldStandardName } else { t.name }
|
|
this.reference_sequence = t.reference
|
|
this.DBSNP = new File("/humgen/gsa-hpprojects/GATK/data/dbsnp_129_" + t.rodName + ".rod")
|
|
this.rodBind :+= RodBind("hapmap", "VCF", "/humgen/gsa-hpprojects/GATK/data/Comparisons/Validated/HapMap/3.2/genotypes_r27_nr." + t.rodName + "_fwd.vcf")
|
|
if(t.trainOmni == 0) {
|
|
this.rodBind :+= RodBind("1kg", "VCF", "/humgen/gsa-hpprojects/GATK/data/Comparisons/Unvalidated/1kg_pilot1_projectCalls/ALL.low_coverage.2010_07.hg19.vcf")
|
|
this.rodBind :+= RodBind("truth", "VCF", "/humgen/gsa-hpprojects/GATK/data/Comparisons/Validated/HapMap/3.2/genotypes_r27_nr." + t.rodName + "_fwd.vcf")
|
|
} else {
|
|
this.rodBind :+= RodBind("1kg", "VCF", "/humgen/gsa-hpprojects/GATK/data/Comparisons/Validated/Omni2.5_chip/764samples.deduped.b37.annot.vcf")
|
|
this.rodBind :+= RodBind("truth", "VCF", "/humgen/gsa-hpprojects/GATK/data/Comparisons/Validated/Omni2.5_chip/764samples.deduped.b37.annot.vcf")
|
|
}
|
|
this.rodBind :+= RodBind("input", "VCF", if ( goldStandard ) { t.goldStandard_VCF } else { t.filteredVCF } )
|
|
this.clusterFile = if ( goldStandard ) { t.goldStandardClusterFile } else { t.clusterFile }
|
|
//this.use_annotation ++= List("QD", "SB", "HaplotypeScore", "HRun")
|
|
if(t.useQD == 1) {
|
|
this.use_annotation ++= List("QD")
|
|
}
|
|
if(t.useSB == 1) {
|
|
this.use_annotation ++= List("SB")
|
|
}
|
|
if(t.useHS == 1) {
|
|
this.use_annotation ++= List("HaplotypeScore1")
|
|
}
|
|
if(t.useHRUN == 1) {
|
|
this.use_annotation ++= List("HRun")
|
|
}
|
|
if(t.useMQRST == 1) {
|
|
this.use_annotation ++= List("MQRankSum")
|
|
}
|
|
if(t.useBQRST == 1) {
|
|
this.use_annotation ++= List("BaseQRankSum")
|
|
}
|
|
if(t.useGC == 1) {
|
|
this.use_annotation ++= List("GC")
|
|
}
|
|
if(t.useMQ == 1) {
|
|
this.use_annotation ++= List("MQ")
|
|
}
|
|
if(t.useSumGL == 1) {
|
|
this.use_annotation ++= List("sumGLbyD+")
|
|
}
|
|
if( t.useQD==0 && t.useSB==0 && t.useHS==0 && t.useHRUN==0 && t.useMQRST==0 && t.useBQRST==0 && t.useGC==0 && t.useMQ==0 && t.useSumGL==0) {
|
|
this.use_annotation ++= List("MQ","QD","DP")
|
|
}
|
|
this.analysisName = name + "_GVC"
|
|
this.intervalsString ++= List(t.intervals)
|
|
this.qual = Some(t.qualCutoff)
|
|
this.std = Some(t.std)
|
|
this.mG = Some(t.gaussian)
|
|
this.ignoreFilter ++= FiltersToIgnore
|
|
this.dirichlet = Some(t.dirichlet)
|
|
this.shrinkage = Some(t.shrinkage)
|
|
}
|
|
|
|
// 4.) VQSR part2 Calculate new LOD for all input SNPs by evaluating the Gaussian clusters
|
|
class VariantRecalibratorBase(t: Target, goldStandard: Boolean) extends org.broadinstitute.sting.queue.extensions.gatk.VariantRecalibrator with UNIVERSAL_GATK_ARGS {
|
|
val name: String = if ( goldStandard ) { t.goldStandardName } else { t.name }
|
|
this.reference_sequence = t.reference
|
|
this.DBSNP = new File("/humgen/gsa-hpprojects/GATK/data/dbsnp_129_" + t.rodName + ".rod")
|
|
this.rodBind :+= RodBind("hapmap", "VCF", "/humgen/gsa-hpprojects/GATK/data/Comparisons/Validated/HapMap/3.2/genotypes_r27_nr." + t.rodName + "_fwd.vcf")
|
|
if(t.trainOmni == 0) {
|
|
this.rodBind :+= RodBind("1kg", "VCF", "/humgen/gsa-hpprojects/GATK/data/Comparisons/Unvalidated/1kg_pilot1_projectCalls/ALL.low_coverage.2010_07.hg19.vcf")
|
|
this.rodBind :+= RodBind("truth", "VCF", "/humgen/gsa-hpprojects/GATK/data/Comparisons/Validated/HapMap/3.2/genotypes_r27_nr." + t.rodName + "_fwd.vcf")
|
|
} else {
|
|
this.rodBind :+= RodBind("1kg", "VCF", "/humgen/gsa-hpprojects/GATK/data/Comparisons/Validated/Omni2.5_chip/764samples.deduped.b37.annot.vcf")
|
|
this.rodBind :+= RodBind("truth", "VCF", "/humgen/gsa-hpprojects/GATK/data/Comparisons/Validated/Omni2.5_chip/764samples.deduped.b37.annot.vcf")
|
|
}
|
|
this.rodBind :+= RodBind("input", "VCF", if ( goldStandard ) { t.goldStandard_VCF } else { t.filteredVCF } )
|
|
this.clusterFile = if ( goldStandard ) { t.goldStandardClusterFile } else { t.clusterFile }
|
|
this.analysisName = name + "_VR"
|
|
this.intervalsString ++= List(t.intervals)
|
|
this.ignoreFilter ++= FiltersToIgnore
|
|
this.ignoreFilter ++= List("HARD_TO_VALIDATE")
|
|
this.target_titv = Some(t.titvTarget)
|
|
this.backOff = Some(t.backoff)
|
|
}
|
|
|
|
// 4a.) Choose VQSR tranches based on novel ti/tv
|
|
class VariantRecalibratorTiTv(t: Target, goldStandard: Boolean) extends VariantRecalibratorBase(t, goldStandard) {
|
|
this.tranche ++= List("1.0")
|
|
this.out = new File("/dev/null")
|
|
val tranchesName: String = "%s_%d_%.4f_%.4f_%.1f_%d_%.1f_%d%d%d%d%d%d%d%d%d_%d.titv.tranches".format(this.name, t.gaussian, t.shrinkage, t.dirichlet, t.backoff, t.qualCutoff, t.std, t.useQD, t.useSB, t.useHS, t.useHRUN, t.useMQRST, t.useBQRST, t.useGC, t.useMQ, t.useSumGL, t.trainOmni)
|
|
this.tranchesFile = new File(tranchesName)
|
|
}
|
|
|
|
// 4b.) Choose VQSR tranches based on sensitivity to truth set
|
|
class VariantRecalibratorNRS(t: Target, goldStandard: Boolean) extends VariantRecalibratorBase(t, goldStandard) {
|
|
this.sm = Some(org.broadinstitute.sting.gatk.walkers.variantrecalibration.VariantRecalibrator.SelectionMetricType.TRUTH_SENSITIVITY)
|
|
if(t.trainOmni == 0 ) {
|
|
this.tranche ++= List("1.0")
|
|
} else {
|
|
this.tranche ++= List("2.5")
|
|
}
|
|
this.out = new File("/dev/null")
|
|
val tranchesName: String = "%s_%d_%.4f_%.4f_%.1f_%d_%.1f_%d%d%d%d%d%d%d%d%d_%d.ts.tranches".format(this.name, t.gaussian, t.shrinkage, t.dirichlet, t.backoff, t.qualCutoff, t.std, t.useQD, t.useSB, t.useHS, t.useHRUN, t.useMQRST, t.useBQRST, t.useGC, t.useMQ, t.useSumGL, t.trainOmni)
|
|
this.tranchesFile = new File(tranchesName)
|
|
}
|
|
}
|