V1 of the data processing paper, produced results for the manuscript we presented. Commit for archival purposes
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@4648 348d0f76-0448-11de-a6fe-93d51630548a
This commit is contained in:
depristo
parent
2f3be24a00
commit
0e062ae040
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from farm_commands2 import *
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import os.path
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import sys
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from optparse import OptionParser
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from datetime import date
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import glob
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import operator
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import faiReader
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import math
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import shutil
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import string
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from madPipelineUtils import *
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EXCLUDE_CHRS = ['chrM', 'chrY']
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EXTRA_GATK_ARGS = ' -XL chrM -XL chrY -L chr1 ' # -XL chrX -XL chrY '
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#EXTRA_GATK_ARGS = ' -XL chrM -XL chrY ' # -XL chrX -XL chrY '
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VALIDATION_DIR = '/humgen/gsa-hpprojects/GATK/data/Comparisons'
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BAM_ROOT = '/humgen/1kg/analysis/bamsForDataProcessingPapers/'
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WE_LIST = '/seq/references/HybSelOligos/whole_exome_agilent_designed_120/whole_exome_agilent_designed_120.targets.interval_list'
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WGS_FILTER = [['ABFilter', 'AB > 0.75 && DP > 40'], ['DPFilter', 'DP > 120 || SB > -0.10']] # , ['QDFilter', 'QD < 5.0 && DP > 40']]
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WE_FILTER = [['ESPStandard', 'AB > 0.75 || QD < 5.0 || HRun > 3 || SB > -0.10']]
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UG_ARGS = "-mbq 20 -mmq 20 -stand_call_conf 30 -stand_emit_conf 10 -hets 0.78e-3 -mrl 10000"
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class CallTarget:
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def __init__(self, name, bam, interval = '', callArgs = "", b36 = False, optimize = True, filters = [], targetTiTv = 2.07, maxClusters = 16, minQual = 300, tranchToTake = 0.1):
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self.name = name
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self.bam = bam
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self.interval = interval
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self.callArgs = callArgs
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self.vcfs = [] # list of processed vcf
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self.b36 = b36
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self.filters = filters
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self.optimize = optimize
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self.targetTiTv = targetTiTv
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self.maxClusters = maxClusters
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self.tranchToTake = tranchToTake
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self.minQual = minQual
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def getCallArgs(self):
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return self.callArgs # + self.getIntervalArg()
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def getIntervalArg(self):
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if self.hasInterval():
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return ' -L ' + self.interval
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else:
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return ''
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def hasInterval(self):
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return self.interval != '' and self.interval != None
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def getVcf(self):
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return os.path.join(OPTIONS.dir, self.name + ".vcf")
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def getVcfs(self):
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return self.vcfs
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def addVcf(self, vcf):
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self.vcfs.append(vcf)
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def getBam(self):
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return self.bam
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KG_PATH = '/humgen/gsa-hpprojects/1kg/1kg_pilot2/currentBestProjectCalls'
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TECH_COMP = '/humgen/gsa-hphome1/kiran/one_off_projects/multiTechComparisons/results/v7/NA12878'
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#WGS_INTERVAL = 'chr1'
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#WGS_INTERVAL = '-L chr1:1-50,000,000'
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def weTarget(name, bam, ignore = '', args = '', filters = None):
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return CallTarget(name, bam, interval = WE_LIST, callArgs = args, filters = WE_FILTER, targetTiTv = 3.0, maxClusters = 8, minQual = 2800, tranchToTake = 10)
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#TARGETS_BY_STRATEGY = [['', ''], ['.OQ', '-OQ'], ['.OQ.noCM', '-OQ -bm THREE_STATE'], ['.noCM', '-bm THREE_STATE']]
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TARGETS_BY_STRATEGY = [['', ''], ['.OQ', '-OQ']]
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#TARGETS_BY_STRATEGY = [['', '']]
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def targetsByStrategy(func, rootName, bam, interval = '', args = '', filters = []):
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def makeTarget(ext, moreArgs):
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name = rootName + ext
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return func(name, bam, interval, args + ' ' + moreArgs, filters = filters)
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if "cleaned" in rootName or "CG" in rootName:
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strats = [TARGETS_BY_STRATEGY[0]]
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else:
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strats = [TARGETS_BY_STRATEGY[1]]
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return map(lambda x: makeTarget(*x), strats)
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targets = []
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def findTargets(names):
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def find1(name):
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for target in targets:
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if target.name == name:
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return target
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return None
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return map(find1, names)
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def matches(string, pattern):
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return string.find(pattern) != -1
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def main():
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global OPTIONS, targets
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usage = "usage: %prog stage [options]"
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parser = OptionParser(usage=usage)
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parser.add_option("", "--dry", dest="dry",
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action='store_true', default=False,
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help="If provided, nothing actually gets run, just a dry run")
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parser.add_option("-v", "--verbose", dest="verbose",
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action='store_true', default=False,
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help="If provided, print out a lot of information")
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parser.add_option("", "--byQEval", dest="byQEval",
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action='store_true', default=False,
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help="If provided, variant eval will be run by Q threshold")
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parser.add_option("-s", "--splitByChr", dest="splitByChr",
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action='store_true', default=False,
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help="If provided, we'll parallelize by chromosome over the farm")
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parser.add_option("", "--dev", dest="dev",
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action='store_true', default=False,
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help="If provided, we'll use the GATK dev build")
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parser.add_option("-d", "--dir", dest="dir",
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type='string', default="",
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help="If provided, this is the root where files are read and written")
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parser.add_option("-L", "", dest="WGSIntervals",
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type='string', default=None,
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help="If provided, these are the interval files we will process for WGS")
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parser.add_option("-q", "--farm", dest="farmQueue",
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type="string", default=None,
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help="Farm queue to send processing jobs to")
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parser.add_option("-p", "--parallel", dest="parallel",
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type="int", default=None,
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help="Number of parallel shared memory threads")
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parser.add_option("-t", "--target", dest="target",
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type="string", default=None,
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help="Only run jobs with names containing this string")
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(OPTIONS, args) = parser.parse_args()
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if len(args) != 1:
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parser.error("incorrect number of arguments")
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# set up targets
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# WGS
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WGS_INTERVAL = OPTIONS.WGSIntervals
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#targets += targetsByStrategy(CallTarget, 'GA2.WGS.cleaned', BAM_ROOT + '/NA12878.GA2.WGS.bwa.cleaned.bam', WGS_INTERVAL, filters = WGS_FILTER)
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#targets.append(CallTarget('GA2.WGS.raw', '/seq/dirseq/pem/seq/picard_aggregation/G2946gaII/NA12878/v1/NA12878.bam', WGS_INTERVAL, filters = WGS_FILTER))
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# HiSeq
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targets += targetsByStrategy(CallTarget, 'HiSeq.WGS.raw', '/seq/dirseq/pem/seq/picard_aggregation/G2946/NA12878/v1/NA12878.bam', WGS_INTERVAL, filters = WGS_FILTER)
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targets += targetsByStrategy(CallTarget, 'HiSeq.WGS.cleaned', '/humgen/1kg/analysis/bamsForDataProcessingPapers/scriptsToMakeBams/tmp.list', WGS_INTERVAL, filters = WGS_FILTER)
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#targets += targetsByStrategy(CallTarget, 'HiSeq.WGS.cleaned', '/humgen/1kg/analysis/bamsForDataProcessingPapers/highpass_v3/NA12878.HiSeq.WGS.bwa.cleaned.bam', WGS_INTERVAL, filters = WGS_FILTER)
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# targets += targetsByStrategy(CallTarget, 'HiSeq.WGS.cleaned', BAM_ROOT + '/NA12878.HiSeq.WGS.bwa.cleaned.recal.bam', WGS_INTERVAL, filters = WGS_FILTER)
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# WE
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targets += targetsByStrategy(weTarget, 'GA2.WEx.cleaned', BAM_ROOT + '/NA12878.WEx.cleaned.recal.bam')
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targets += targetsByStrategy(weTarget, 'GA2.WEx.raw', '/seq/picard_aggregation/C308/NA12878/v3/NA12878.bam')
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#targets.append(weTarget('GA2.WEx.raw', '/seq/picard_aggregation/C308/NA12878/v3/NA12878.bam'))
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targets += targetsByStrategy(CallTarget, 'CG.WGS.raw', '/seq/complete_genomics/GS00106-DNA_E01-180_NA12878/SAM0/merge/NA12878.bam', WGS_INTERVAL, filters = WGS_FILTER)
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# CG
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# todo -- fixme -- needs genome-wide bams on hg18
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#targets.append(CallTarget('CG.chr1.raw', '/humgen/gsa-hphome1/kiran/one_off_projects/multiTechComparisons/results/v5/NA12878/CG.full/sample.chr1.primaryAlignmentsMarked.dupesRemoved.bam', WGS_INTERVAL, filters = WGS_FILTER, callArgs = "-bm THREE_STATE", b36 = True))
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# low-pass
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# '/humgen/gsa-hpprojects/1kg/1kg_pilot1/freeze5_merged/low_coverage_CEU.1.bam
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# targets.append(CallTarget('CEU.lowpass.cleaned', 'CEU.bam.list', WGS_INTERVAL, b36 = True))
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# 1KG SLX
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# targets.append(CallTarget('1KG.NA12878', '/humgen/gsa-hpprojects/1kg/1kg_pilot2/useTheseBamsForAnalyses/NA12878.SLX.bam', WGS_INTERVAL, b36 = True))
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# MCDK1 special case
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#MCKD1_INTERVAL = "chr1:152448527-154998173"
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#targets.append(CallTarget('MCKD1.raw', '/humgen/gsa-hpprojects/dev/depristo/oneOffProjects/MCKD1_WGS/MCKD1.bam.list', MCKD1_INTERVAL, filters = WGS_FILTER, callArgs = '-bm THREE_STATE'))
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#targets.append(CallTarget('MCKD1.cleaned', '/humgen/gsa-hpprojects/dev/depristo/oneOffProjects/MCKD1_WGS/bams_linkage/MCKD1.bam.cleaned.bam.chr1:152448527-154998173.bam', MCKD1_INTERVAL, filters = WGS_FILTER, callArgs = '-bm THREE_STATE'))
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stages = map(string.lower, args[0].split(","))
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STAGES = ['callsnps', 'callindels', 'indelmask', 'snpfilter', 'indelfilter', 'to_hg18', 'optimize', 'eval', 'confusion_matrix']
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for stage in stages:
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if stage not in STAGES:
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sys.exit('unknown stage ' + stage)
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if OPTIONS.dir != "" and not os.path.exists(OPTIONS.dir):
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os.makedirs(OPTIONS.dir)
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allJobs = []
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def includeStage(name):
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return name in stages
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for callTarget in targets:
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# setup pipeline args
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GATK_JAR = GATK_STABLE_JAR
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if ( OPTIONS.dev ): GATK_JAR = GATK_DEV_JAR
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myPipelineArgs = PipelineArgs(GATK_JAR = GATK_JAR, name = callTarget.name, excludeChrs = EXCLUDE_CHRS)
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myPipelineArgs.addGATKArg(EXTRA_GATK_ARGS)
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myPipelineArgs.addGATKArg(callTarget.getIntervalArg())
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if ( OPTIONS.parallel != None ): myPipelineArgs.addGATKArg(' -nt ' + OPTIONS.parallel)
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if ( callTarget.b36 ): myPipelineArgs.ref = 'b36'
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print callTarget.name, callTarget.b36, myPipelineArgs.ref
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lastJobs = None
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if OPTIONS.target != None and not matches(callTarget.name, OPTIONS.target):
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print 'Skipping target', callTarget
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continue
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def updateNewJobs(newjobs, lastJobs):
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if OPTIONS.verbose:
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print 'New jobs', newjobs
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#for job in newjobs:
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# print ' job ', job
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allJobs.append(newjobs)
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if newjobs != []:
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lastJobs = newjobs
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return [], lastJobs
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newJobs = []
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def execStage(name, func, vcf = None, lastJobs = []):
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if OPTIONS.verbose: print 'Name is', name
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newJobs, newVcf = func(myPipelineArgs, callTarget, vcf, lastJobs)
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if newVcf != None: vcf = newVcf
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if OPTIONS.verbose: print 'VCF is', vcf
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callTarget.addVcf(vcf)
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if includeStage(name): newJobs, lastJobs = updateNewJobs(newJobs, lastJobs)
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if OPTIONS.verbose: print 'execStage:', newJobs, lastJobs, vcf
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return newJobs, lastJobs, vcf
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newJobs, callSNPJobs, vcf = execStage('callsnps', callSNPs)
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newJobs, lastJobs, vcf = execStage('to_hg18', convertToHg18, vcf, callSNPJobs)
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newJobs, filterSNPJobs, vcf = execStage('snpfilter', filterSNPs, vcf, callSNPJobs)
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# indel jobs
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newJobs, callIndelJobs, vcf = execStage('callindels', callIndels, vcf)
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newJobs, indelMaskJobs, vcf = execStage('indelmask', createIndelMask, vcf, callIndelJobs)
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newJobs, filterIndelJobs, vcf = execStage('indelfilter', filterIndels, vcf, indelMaskJobs + filterSNPJobs)
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# optimization
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newJobs, optimizeJobs, vcf = execStage('optimize', VariantOptimizer, vcf, filterIndelJobs)
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# eval
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newJobs, evalJobs, vcf = execStage('eval', evalSNPs, vcf, optimizeJobs)
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# newJobs, lastJobs, ignore = execStage('confusion_matrix', computeConfusionMatrix, vcf)
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print 'EXECUTING JOBS'
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executeJobs(allJobs, farm_queue = OPTIONS.farmQueue, just_print_commands = OPTIONS.dry)
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#
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# Actual commands
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#
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def convertToHg18( myPipelineArgs, callTarget, vcf, lastJobs ):
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if callTarget.b36:
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outputVCF = vcf.replace(".b36", "")
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cmd = 'python /humgen/gsa-scr1/depristo/dev/GenomeAnalysisTK/trunk/python/vcf_b36_to_hg18.py ' + vcf + ' ' + outputVCF
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jobs = [FarmJob(cmd, jobName = callTarget.name + '.' + 'b36ToHg18', dependencies = lastJobs)]
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return jobs, outputVCF
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else:
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return [], vcf
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def callSNPs( myPipelineArgs, callTarget, ignore, lastJobs ):
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outputVCF = appendExtension(callTarget.getVcf(), "ug")
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if callTarget.b36:
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outputVCF = appendExtension(outputVCF, "b36")
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print 'outputVCF', outputVCF
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ugArgs = '-T UnifiedGenotyper -D /humgen/gsa-scr1/GATK_Data/dbsnp_129_hg18.rod -I %s %s -varout %s %s' % (callTarget.getBam(), UG_ARGS, outputVCF, callTarget.getCallArgs())
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farmCmds = simpleGATKCommand( myPipelineArgs, 'UG', ugArgs, lastJobs )
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if OPTIONS.splitByChr and not callTarget.hasInterval():
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farmCmds = splitGATKCommandByChr( myPipelineArgs, farmCmds[0], [outputVCF], [mergeVCFs] )
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return farmCmds, outputVCF
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INDEL_MASK_SIZE = 10
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def getIndelCallFiles(callTarget):
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outputBed = appendExtension(callTarget.getVcf(), "indels.bed", False)
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outputVerbose = appendExtension(callTarget.getVcf(), "indels.verbose.txt", False)
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outputMask = appendExtension(callTarget.getVcf(), "indels.%d.mask" % INDEL_MASK_SIZE, False)
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return outputBed, outputVerbose, outputMask
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def callIndels( myPipelineArgs, callTarget, ignore, lastJobs ):
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outputBed, outputVerbose, outputMask = getIndelCallFiles(callTarget)
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IGV2_ARGS = '-T IndelGenotyperV2 -ws 500 -I %s -O %s -o %s --verbose -rf Platform454' % (callTarget.getBam(), outputBed, outputVerbose)
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farmCmds = simpleGATKCommand( myPipelineArgs, 'CallIndels', IGV2_ARGS, lastJobs )
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if OPTIONS.splitByChr and not callTarget.hasInterval():
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farmCmds = splitGATKCommandByChr( myPipelineArgs, farmCmds[0], [outputBed, outputVerbose], [mergeByCat, mergeByCat] )
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return farmCmds, None
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def createIndelMask( myPipelineArgs, callTarget, vcf, lastJobs ):
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outputBed, outputVerbose, outputMask = getIndelCallFiles(callTarget)
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cmd = 'python /humgen/gsa-scr1/depristo/dev/GenomeAnalysisTK/trunk/python/makeIndelMask.py %s %d %s' % (outputBed, INDEL_MASK_SIZE, outputMask)
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jobs = [FarmJob(cmd, jobName = callTarget.name + '.' + 'makeIndelMask', dependencies = lastJobs)]
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return jobs, None
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def filterSNPs(myPipelineArgs, callTarget, vcf, lastJobs ):
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out = appendExtension(vcf, 'snpfiltered')
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filterString = ' '.join(map(lambda x: '--filterName %s --filterExpression "%s"' % (x[0], x[1]), callTarget.filters))
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return simpleGATKCommand( myPipelineArgs, 'filterSNPs', '-T VariantFiltration -B variant,VCF,%s -o %s --filterName LowQual --filterExpression "QUAL < 50.0" --clusterWindowSize 10 --filterName HARD_TO_VALIDATE --filterExpression "MQ0 >= 4 && ((MQ0 / (1.0 * DP)) > 0.1)" %s' % ( vcf, out, filterString ), lastJobs ), out
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def filterIndels(myPipelineArgs, callTarget, vcf, lastJobs ):
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out = appendExtension(vcf, 'indelfiltered')
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outputBed, outputVerbose, outputMask = getIndelCallFiles(callTarget)
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return simpleGATKCommand( myPipelineArgs, 'filterIndels', '-T VariantFiltration -B variant,VCF,%s -o %s --maskName Indel -B mask,Bed,%s' % ( vcf, out, outputMask ), lastJobs ), out
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def VariantOptimizer( myPipelineArgs, callTarget, vcf, lastJobs ):
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if callTarget.optimize:
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clusterFile = appendExtension(vcf, 'optimized', False)
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optOutVCF = appendExtension(vcf, 'optimized')
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out = appendExtension(vcf, 'optimized.cut')
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table = appendExtension(vcf, 'optimized.table', False)
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#NCLUSTERS = 4
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#ITERATIONS = 3
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#ITERATION_TO_TAKE = ITERATIONS
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DBSNP_PRIOR = 2.0 # dbSNP seems dodger and dodger
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IGNORE_FILTERS_CLUSTERING = "-ignoreFilter DPFilter -ignoreFilter ABFilter -ignoreFilter ESPStandard"
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#IGNORE_FILTERS_CLUSTERING = "-ignoreFilter DPFilter -ignoreFilter ABFilter -ignoreFilter LowQual -ignoreFilter ESPStandard"
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IGNORE_FILTERS_SCORING = IGNORE_FILTERS_CLUSTERING + " -ignoreFilter HARD_TO_VALIDATE"
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annotationsToOptimize = ['SB', 'HaplotypeScore', "QD", 'HRun']
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annotationsToOptimizeArg = ' '.join(map(lambda x: '-an ' + x, annotationsToOptimize)) # '' ['DP', 'SB', 'HaplotypeScore', 'MQ', "QD", 'HRun']
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#tranches = ' '.join(map( lambda x: '-tranche ' + str(x), [1, 5, 10]))
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tranches = ' '.join(map( lambda x: '-tranche ' + str(x), [0.1, 1, 2, 10]))
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maxVariantsToShow = 2500
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#singletonFPRate = 0.2
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REGENERATE_VARIANT_CLUSTERS = True
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if ( REGENERATE_VARIANT_CLUSTERS ):
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jobs1 = simpleGATKCommand( myPipelineArgs, 'GenerateVariantClusters', '-T GenerateVariantClusters -qual %d -std 3.5 -mG %d -D /humgen/gsa-scr1/GATK_Data/dbsnp_129_hg18.rod -B input,VCF,%s -clusterFile %s %s %s' % ( callTarget.minQual, callTarget.maxClusters, vcf, clusterFile, annotationsToOptimizeArg, IGNORE_FILTERS_CLUSTERING ), lastJobs )
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else:
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jobs1 = lastJobs
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jobs2 = simpleGATKCommand( myPipelineArgs, 'VariantRecalibrator', '-T VariantRecalibrator -D /humgen/gsa-scr1/GATK_Data/dbsnp_129_hg18.rod -qStep 0.01 -B input,VCF,%s -clusterFile %s -output %s --target_titv %f %s -resources ~/dev/GenomeAnalysisTK/trunk/R/ %s --known_prior %.2f' % ( vcf, clusterFile, os.path.splitext(optOutVCF)[0], callTarget.targetTiTv, IGNORE_FILTERS_SCORING, tranches, DBSNP_PRIOR ), jobs1 )
|
||||
|
||||
cmd21 = 'python /humgen/gsa-scr1/depristo/dev/GenomeAnalysisTK/trunk/python/vcf2table.py -f CHROM,POS,ID,AC,AF,AN,DB,' + ','.join(annotationsToOptimize) + ' ' + vcf + ' -o ' + table
|
||||
jobs21 = [FarmJob(cmd21, jobName = callTarget.name + '.' + 'VariantRecalibrationReport.vcf2table', dependencies = jobs2)]
|
||||
|
||||
cmd22 = 'Rscript /humgen/gsa-scr1/depristo/dev/GenomeAnalysisTK/trunk/R/VariantRecalibratorReport/VariantRecalibratorReport.R %s %s %s NA %d' % (clusterFile, clusterFile, table, maxVariantsToShow)
|
||||
jobs22 = [FarmJob(cmd22, jobName = callTarget.name + '.' + 'VariantRecalibrationReport.RScript', dependencies = jobs21)]
|
||||
|
||||
jobs3 = simpleGATKCommand( myPipelineArgs, 'ApplyVariantCuts', '-T ApplyVariantCuts -D /humgen/gsa-scr1/GATK_Data/dbsnp_129_hg18.rod -B input,VCF,%s -outputVCF %s --tranchesFile %s.dat.tranches --fdr_filter_level %f' % ( optOutVCF, out, clusterFile, callTarget.tranchToTake ), jobs2 )
|
||||
return jobs1 + jobs2 + jobs21 + jobs22 + jobs3, out
|
||||
else:
|
||||
return [], vcf
|
||||
|
||||
def computeConfusionMatrix(myPipelineArgs, callTarget, vcf, lastJobs ):
|
||||
out = appendExtension(vcf, 'confusionmatrix', addExtension=False)
|
||||
CM_ARGS = '-T ComputeConfusionMatrix -I %s -o %s' % (callTarget.getBam(), out)
|
||||
farmCmds = simpleGATKCommand( myPipelineArgs, 'ConfusionMatrix', CM_ARGS, lastJobs )
|
||||
return farmCmds, None
|
||||
|
||||
def evalSNPs(myPipelineArgs, callTarget, vcf, lastJobs):
|
||||
evalRoot = OPTIONS.dir
|
||||
|
||||
oldMemory = myPipelineArgs.memory
|
||||
myPipelineArgs.memory = '2g'
|
||||
def eval1(vcf, namePostfix = "", args = ""):
|
||||
out = os.path.join(OPTIONS.dir, os.path.basename(vcf) + namePostfix + ".ve2")
|
||||
#validation_bindings = "-B comp_p2_val,VCF," + VALIDATION_DIR + "/Validated/1kg_snp_validation/batch1-2.HG18.vcf -B comp_CG,VCF," + VALIDATION_DIR + "CG.vcf"
|
||||
maybeHiSeqBindings = ""
|
||||
hiSeqComp = os.path.join(OPTIONS.dir,"HiSeq.WGS.cleaned.ug.snpfiltered.indelfiltered.optimized.cut.vcf")
|
||||
omni = " -B compOmni,VCF,omni.na12878.hg18.vcf"
|
||||
if os.path.exists(hiSeqComp):
|
||||
maybeHiSeqBindings = "-B comp_HiSeq,VCF," + hiSeqComp + " "
|
||||
validation_bindings = maybeHiSeqBindings + "-B comp_p2_val,VCF,1kg_pilot2_snps.hg18.vcf -B comp_CG,VCF,/humgen/gsa-hpprojects/GATK/data/Comparisons/Unvalidated/NA12878/CG.hg18.vcf -B compTrio,VCF,CEU.trio.2010_03.genotypes.vcf -B compTrioNovel,VCF,CEU.trio.novels.2010_03.genotypes.vcf -B comp_hm3,VCF,/humgen/gsa-hpprojects/GATK/data/Comparisons/Validated/HapMap/3.2/by_population/genotypes_CEU_phase3.2_consensus.hg18_fwd.vcf -B compDeNovo,VCF,/humgen/gsa-hpprojects/GATK/data/Comparisons/Validated/1kg_denovos/ceu_merged_validation_data_240610.annotated.hg18.vcf -B comp1KGCEU,VCF,YRI.low_coverage.2010_07.sites.vcf" + omni # not in hg18 space :-(
|
||||
tranches = ""
|
||||
if vcf.find("optimized") != -1:
|
||||
args += " -tf " + appendExtension(vcf.replace(".cut", ""), 'dat.tranches', False)
|
||||
vcf = appendExtension(vcf.replace(".cut", ""), 'vcf', False)
|
||||
gatk_args = ("-T VariantEval -reportType Grep -D /humgen/gsa-scr1/GATK_Data/dbsnp_129_hg18.rod -B eval,VCF,%s " + validation_bindings + " -sample NA12878 -o %s -E CompOverlap -E GenotypeConcordance -E TiTvVariantEvaluator -E CountVariants %s") % ( vcf, out, args )
|
||||
#gatk_args = ("-T VariantEval -reportType Grep -D /humgen/gsa-scr1/GATK_Data/dbsnp_129_hg18.rod -select \"hetCount == 1\" -selectName HET -select \"homVarCount == 1\" -selectName HOMVAR -B eval,VCF,%s " + validation_bindings + " -sample NA12878 -select \"QUAL <= 30.0\" -selectName LowQual -o %s -E CompOverlap -E GenotypeConcordance -E TiTvVariantEvaluator -E CountVariants %s") % ( vcf, out, args )
|
||||
|
||||
name = "EVAL_%s_%s" % (callTarget.name, namePostfix)
|
||||
# return FarmJob(cmd, jobName = "EVAL_%s_%s" % (callTarget.name, namePostfix), dependencies = lastJobs)
|
||||
return simpleGATKCommand( myPipelineArgs, name, gatk_args, lastJobs )[0]
|
||||
|
||||
jobs = []
|
||||
for vcf in callTarget.getVcfs():
|
||||
jobs.append(eval1(vcf))
|
||||
if OPTIONS.byQEval and vcf.find("optimized") != -1:
|
||||
for Q in [0.01, 0.02, 0.03, 0.03]:
|
||||
jobs.append(eval1(vcf, '.Q' + str(Q), '-Q ' + str(Q)))
|
||||
|
||||
myPipelineArgs.memory = oldMemory
|
||||
return jobs, None
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
Loading…
Reference in New Issue