continuing improvements in output of snpSelector
git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@2198 348d0f76-0448-11de-a6fe-93d51630548a
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depristo
parent
21a9a717e4
commit
c93d37d9fb
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@ -181,10 +181,13 @@ def compareFieldValues( v1, v2 ):
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return c
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def calculateBins(variants, field, minValue, maxValue, partitions):
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sortedVariants = sorted(variants, key = lambda x: x.getField(field)) # cmp = compareFieldValues,
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sortedValues = map(lambda x: x.getField(field), sortedVariants)
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values = map(lambda x: x.getField(field), variants)
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return calculateBinsForValues(values, field, minValue, maxValue, partitions)
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def calculateBinsForValues(values, field, minValue, maxValue, partitions):
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sortedValues = sorted(values)
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targetBinSize = len(variants) / (1.0*partitions)
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targetBinSize = len(values) / (1.0*partitions)
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#print sortedValues
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uniqBins = groupby(sortedValues)
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binsAndSizes = map(lambda x: [x[0], len(list(x[1]))], uniqBins)
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@ -234,14 +237,14 @@ def validateBins(bins):
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def printFieldQualHeader():
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more = ""
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if TRUTH_CALLS <> None:
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more = "TP FP FPRate FN FNRate"
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more = CallCmp.HEADER
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def p(stream):
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if stream <> None:
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print >> stream, ' field left right nVariants nNovels titv titvNovels dbSNP fprate q', more
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print >> stream, ' %20s %20s left right nVariants nNovels titv titvNovels dbSNP FPEstimate Q' % ("category", "field"), more
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p(sys.stdout)
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p(RECAL_LOG)
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def printFieldQual( field, left, right, variants, FPRate ):
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def printFieldQual( category, field, left, right, variants, FPRate ):
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more = ""
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if TRUTH_CALLS <> None:
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callComparison, theseFPs = sensitivitySpecificity(variants, TRUTH_CALLS)
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@ -249,7 +252,7 @@ def printFieldQual( field, left, right, variants, FPRate ):
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novels = selectVariants(variants, VCFRecord.isNovel)
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def p(stream):
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if stream <> None:
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print >> stream, ' %s %s %8d %8d %.2f %.2f %.2f %.2e %d' % (field, binString(left, right), len(variants), len(novels), titv(variants), titv(novels), dbSNPRate(variants), FPRate, phredScale(FPRate)), more
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print >> stream, ' %20s %20s %s %8d %8d %.2f %.2f %.2f %.2e %3d' % (category, field, binString(left, right), len(variants), len(novels), titv(variants), titv(novels), dbSNPRate(variants), FPRate, phredScale(FPRate)), more
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p(sys.stdout)
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p(RECAL_LOG)
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@ -265,7 +268,7 @@ def binString(left, right):
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#
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#
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def recalibrateCalls(variants, fields, callCovariates):
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def phred(v): return int(round(phredScale(v)))
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def phred(v): return round(phredScale(v), 2)
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for variant in variants:
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recalCall = RecalibratedCall(variant, fields)
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@ -277,7 +280,7 @@ def recalibrateCalls(variants, fields, callCovariates):
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recalCall.recalFeature(callCovariate.getFeature(), FPR)
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recalCall.call.setField(callCovariate.getCovariateField(), phred(FPR))
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#recalCall.call.setField('QUAL', phred(recalCall.jointFPErrorRate()))
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recalCall.call.setField('QUAL', phred(recalCall.jointFPErrorRate()))
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recalCall.call.setField('OQ', originalQual)
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#print 'recalibrating', variant.getLoc()
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@ -288,16 +291,16 @@ def recalibrateCalls(variants, fields, callCovariates):
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#
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#
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def optimizeCalls(variants, fields, titvTarget):
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callCovariates = calibrateFeatures(variants, fields, titvTarget)
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callCovariates = calibrateFeatures(variants, fields, titvTarget, category = "covariates")
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recalCalls = recalibrateCalls(variants, fields, callCovariates)
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return recalCalls, callCovariates
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def printCallQuals(recalCalls, titvTarget, info = ""):
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def printCallQuals(field, recalCalls, titvTarget, info = ""):
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print '--------------------------------------------------------------------------------'
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print info
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calibrateFeatures(recalCalls, ['QUAL'], titvTarget, printCall = True, cumulative = False, forcePrint = True, prefix = "OPT-", printHeader = False )
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calibrateFeatures(recalCalls, [field], titvTarget, printCall = True, cumulative = False, forcePrint = True, prefix = "OPT-", printHeader = False, category = "optimized-calls" )
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print 'Cumulative'
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calibrateFeatures(recalCalls, ['QUAL'], titvTarget, printCall = True, cumulative = True, forcePrint = True, prefix = "OPTCUM-", printHeader = False )
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calibrateFeatures(recalCalls, [field], titvTarget, printCall = True, cumulative = True, forcePrint = True, prefix = "OPTCUM-", printHeader = False, category = "optimized-calls" )
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def all( p, l ):
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for elt in l:
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@ -323,7 +326,7 @@ def mapVariantBins(variants, field, cumulative = False):
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return imap( variantsInBin, bins )
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def calibrateFeatures(variants, fields, titvTarget, printCall = False, cumulative = False, forcePrint = False, prefix = '', printHeader = True ):
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def calibrateFeatures(variants, fields, titvTarget, printCall = False, cumulative = False, forcePrint = False, prefix = '', printHeader = True, category = None ):
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covariates = []
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if printHeader: printFieldQualHeader()
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@ -338,7 +341,7 @@ def calibrateFeatures(variants, fields, titvTarget, printCall = False, cumulativ
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titv, FPRate = titvFPRateEstimate(selectedVariants, titvTarget)
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dbsnp = dbSNPRate(selectedVariants)
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covariates.append(CallCovariate(field, left, right, FPRate))
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printFieldQual( prefix + field, left, right, selectedVariants, FPRate )
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printFieldQual( category, prefix + field, left, right, selectedVariants, FPRate )
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else:
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print 'Not calibrating bin', left, right, 'because it contains too few variants:', len(selectedVariants)
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@ -350,14 +353,24 @@ class CallCmp:
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self.nFP = nFP
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self.nFN = nFN
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def FPRate(self):
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return (1.0*self.nFP) / max(self.nTP + self.nFP, 1)
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# def FPRate(self):
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# return (1.0*self.nFP) / max(self.nTP + self.nFP, 1)
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def FNRate(self):
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return (1.0*self.nFN) / max(self.nTP + self.nFN, 1)
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def sensitivity(self):
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# = TP / (TP + FN)
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return (1.0*self.nTP) / max( self.nTP + self.nFN,1 )
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def PPV(self):
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# = TP / (TP + FP)
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return (1.0*self.nTP) / max( self.nTP + self.nFP, 1 )
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HEADER = "TP FP FN FNRate Sensitivity PPV"
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def __str__(self):
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return '%6d %6d %.2f %6d %.2f' % (self.nTP, self.nFP, self.FPRate(), self.nFN, self.FNRate())
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return '%6d %6d %6d %.2f %.2f %.2f' % (self.nTP, self.nFP, self.nFN, self.FNRate(), self.sensitivity(), self.PPV())
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def variantInTruth(variant, truth):
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if variant.getLoc() in truth:
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@ -386,16 +399,17 @@ def compareCalls(calls, truthCalls):
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for variant in calls: variant.setField("TP", 0) # set the TP field to 0
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def compare1(name, cumulative):
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for left, right, selectedVariants in mapVariantBins(calls, 'QUAL', cumulative = cumulative):
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#print selectedVariants[0]
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printFieldQual(name, left, right, selectedVariants, dephredScale(left))
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for field in ["QUAL", "OQ"]:
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for left, right, selectedVariants in mapVariantBins(calls, field, cumulative = cumulative):
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#print selectedVariants[0]
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printFieldQual("truth-comparison-" + name, field, left, right, selectedVariants, dephredScale(left))
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print 'PER BIN nCalls=', len(calls)
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# printFieldQualHeader()
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compare1('RECAL-QUAL-TRUTH-PER-BIN', False)
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compare1('per-bin', False)
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print 'CUMULATIVE nCalls=', len(calls)
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compare1('RECAL-QUAL-TRUTH-CUMULATIVE', True)
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compare1('cum', True)
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def randomSplit(l, pLeft):
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def keep(elt, p):
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@ -486,11 +500,11 @@ def determineCovariates(allCalls, titvtarget, fields):
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callsToOptimize = allCalls
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recalOptCalls, covariates = optimizeCalls(callsToOptimize, fields, titvtarget)
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printCallQuals(list(recalOptCalls), titvtarget, 'OPTIMIZED CALLS')
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printCallQuals("QUAL", list(recalOptCalls), titvtarget, 'OPTIMIZED CALLS')
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if OPTIONS.bootStrap:
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recalibatedEvalCalls = recalibrateCalls(recalEvalCalls, fields, covariates)
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printCallQuals(list(recalibatedEvalCalls), titvtarget, 'BOOTSTRAP EVAL CALLS')
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printCallQuals("QUAL", list(recalibatedEvalCalls), titvtarget, 'BOOTSTRAP EVAL CALLS')
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return covariates
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@ -562,7 +576,8 @@ def main():
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RecalibratedCalls = recalibrateCalls(callsToRecalibate, fields, covariates)
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writeRecalibratedCalls(OPTIONS.outputVCF, header, RecalibratedCalls)
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else:
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printCallQuals(allCalls, titvTarget)
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printFieldQualHeader()
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printCallQuals("QUAL", allCalls, titvTarget)
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OPTIONS.outputVCF = args[0]
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if len(args) > 1:
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