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minor cleanup 

git-svn-id: file:///humgen/gsa-scr1/gsa-engineering/svn_contents/trunk@2616 348d0f76-0448-11de-a6fe-93d51630548a
This commit is contained in:
depristo 2010-01-16 20:23:20 +00:00
parent d8e74c5795
commit 8226f4aa12
1 changed files with 23 additions and 9 deletions
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32
python/snpSelector.py
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@ -91,7 +91,7 @@ class RecalibratedCall:
def __str__(self):
return '[%s: %s => Q%d]' % (str(self.call), self.featureStringList(), phredScale(self.jointFPErrorRate()))
def readVariants( file, maxRecords = None, decodeAll = True, downsampleFraction = 1, filter = None, minQScore = -1, mustBeVariant = False ):
def readVariants( file, maxRecords = None, decodeAll = True, downsampleFraction = 1, filter = None, minQScore = -1, mustBeVariant = False, skip = None ):
if filter == None:
filter = not OPTIONS.unfiltered
@ -99,9 +99,12 @@ def readVariants( file, maxRecords = None, decodeAll = True, downsampleFraction
header, columnNames, lines = readVCFHeader(f)
nLowQual = 0
counter = 0
def parseVariant(args):
global nLowQual
global nLowQual, counter
header1, VCF, counter = args
counter += 1
#print counter, skip, counter % skip
if filter and not VCF.passesFilters() or ( False and mustBeVariant == True and not VCF.isVariant() ): # currently ignore mustBeVariant
#print 'filtering', VCF
return None
@ -109,6 +112,9 @@ def readVariants( file, maxRecords = None, decodeAll = True, downsampleFraction
#print 'filtering', VCF
#nLowQual += 1
return None
elif skip <> None and counter % skip <> 0:
#print 'skipping'
return None
elif random.random() <= downsampleFraction:
return VCF
else:
@ -481,7 +487,7 @@ def sensitivitySpecificity(variants, truth):
variant.setField("TP", 0)
#print t, variant, "is a FP!"
FPs.append(variant)
nRef = len(filter(lambda x: not x.isVariant(), truth.itervalues()))
nRef = 0 # len(filter(lambda x: not x.isVariant(), truth.itervalues()))
nFN = variantsInTruth(truth.itervalues()) - nTP - nRef
#print 'nRef', nTP, nFP, nFN, nRef
return CallCmp(nTP, nFP, nFN), FPs
@ -571,6 +577,9 @@ def setup():
parser.add_option("-b", "--bootstrap", dest="bootStrap",
type='float', default=None,
help="If provided, the % of the calls used to generate the recalibration tables. [default: %default]")
parser.add_option("-k", "--skip", dest="skip",
type=int, default=None,
help="If provided, we'll only take every nth record [default: %default]")
parser.add_option("-s", "--useSample", dest="useSample",
type='string', default=False,
help="If provided, we will examine sample genotypes for this sample, and consider TP/FP/FN in the truth conditional on sample genotypes [default: %default]")
@ -585,11 +594,15 @@ def setup():
def assessCalls(file):
print 'Counting records in VCF', file
numberOfRecords = quickCountRecords(open(file))
if OPTIONS.maxRecords <> None and OPTIONS.maxRecords < numberOfRecords:
numberOfRecords = OPTIONS.maxRecords
downsampleFraction = min(float(OPTIONS.maxRecordsForCovariates) / numberOfRecords, 1)
header, allCalls = readVariants(file, OPTIONS.maxRecords, downsampleFraction=downsampleFraction, minQScore = OPTIONS.minQScore)
numberOfRecords = 1
downsampleFraction = 1
if OPTIONS.maxRecords <> None:
numberOfRecords = quickCountRecords(open(file))
if OPTIONS.maxRecords < numberOfRecords:
numberOfRecords = OPTIONS.maxRecords
downsampleFraction = min(float(OPTIONS.maxRecordsForCovariates) / numberOfRecords, 1)
#print 'Reading variants', OPTIONS.skip, downsampleFraction
header, allCalls = readVariants(file, OPTIONS.maxRecords, downsampleFraction=downsampleFraction, minQScore = OPTIONS.minQScore, skip = OPTIONS.skip)
allCalls = list(allCalls)
print 'Number of VCF records', numberOfRecords, ', max number of records for covariates is', OPTIONS.maxRecordsForCovariates, 'so keeping', downsampleFraction * 100, '% of records'
print 'Number of selected VCF records', len(allCalls)
@ -684,7 +697,8 @@ def main():
header, allCalls, titvTarget = assessCalls(args[0])
if not OPTIONS.dontRecalibrate:
covariates = determineCovariates(allCalls, titvTarget, fields)
header, callsToRecalibate = readVariants(args[0], OPTIONS.maxRecords, minQScore = OPTIONS.minQScore)
print OPTIONS
header, callsToRecalibate = readVariants(args[0], OPTIONS.maxRecords, minQScore = OPTIONS.minQScore, skip = OPTIONS.skip)
RecalibratedCalls = recalibrateCalls(callsToRecalibate, fields, covariates)
writeRecalibratedCalls(OPTIONS.outputVCF, header, RecalibratedCalls)
else: