def setup(self, **keywords):
"""
2013.09.30
"""
parentClass.setup(self, **keywords)
#. read in alignment coverage data
trioInconsistencyFile = MatrixFile(inputFname=self.originalTrioInconsistencyFname)
trioInconsistencyFile.constructColName2IndexFromHeader()
self.trioID2dataList = trioInconsistencyFile.constructDictionary(keyColumnIndexList=[0], valueColumnIndexList=[1,2,3],\
keyUniqueInInputFile=True)
trioInconsistencyFile.close()
self.alignmentID2alignmentReadGroup = {}
for alignmentReadGroup in self.alignmentReadGroup2individualID:
alignmentID = alignmentReadGroup.split('_')[0]
self.alignmentID2alignmentReadGroup[alignmentID] = alignmentReadGroup
def setup(self, **keywords): """ 2013.09.30 """ parentClass.setup(self, **keywords) #. read in pedigree graph self.plinkPedigreeFile = PlinkPedigreeFile(inputFname=self.pedigreeFname) self.pedigreeGraph = self.plinkPedigreeFile.pedigreeGraph #. read in alignment coverage data alignmentCoverageFile = MatrixFile(inputFname=self.individualAlignmentCoverageFname) alignmentCoverageFile.constructColName2IndexFromHeader() self.alignmentReadGroup2coverage = alignmentCoverageFile.constructDictionary(keyColumnIndexList=[0], valueColumnIndexList=[1],\ keyUniqueInInputFile=True, valueDataType=float) #. also get map from read_group to individual.id (used in graph) alignmentCoverageFile._resetInput() self.alignmentReadGroup2individualID = alignmentCoverageFile.constructDictionary(keyColumnIndexList=[0], valueColumnIndexList=[2], \ keyUniqueInInputFile=True) #. also get map from individual.id to read_group (used in graph) alignmentCoverageFile._resetInput() self.individualID2alignmentReadGroup = alignmentCoverageFile.constructDictionary(keyColumnIndexList=[2], valueColumnIndexList=[0], \ keyUniqueInInputFile=True) alignmentCoverageFile.close()
def run(self):
"""
"""
if self.debug:
import pdb
pdb.set_trace()
reader = MatrixFile(inputFname=self.inputFname)
reader.constructColName2IndexFromHeader()
meanMendelErrorIndex = reader.getColIndexGivenColHeader(
"meanMendelError")
noOfLociIndex = reader.getColIndexGivenColHeader("sampled_base_count")
sumOfMendelErrorIndex = reader.getColIndexGivenColHeader(
"sumOfMendelError")
plinkPedigreeFile = PlinkPedigreeFile(inputFname=self.pedigreeFname)
familyStructureData = plinkPedigreeFile.getFamilyStructurePlinkWay()
twoParentFamilyCountData = self.getNoOfFamiliesAndKidsGivenParentSetSize(noOfParents2FamilyData=familyStructureData.noOfParents2FamilyData, \
parentSetSize=2)
singleParentFamilyCountData = self.getNoOfFamiliesAndKidsGivenParentSetSize(noOfParents2FamilyData=familyStructureData.noOfParents2FamilyData, \
parentSetSize=1)
zeroParentFamilyCountData = self.getNoOfFamiliesAndKidsGivenParentSetSize(noOfParents2FamilyData=familyStructureData.noOfParents2FamilyData, \
parentSetSize=0)
writer = MatrixFile(self.outputFname, openMode='w', delimiter='\t')
header = ["ID", "noOfTotalLoci", \
"noOfTwoParentFamilies", "noOfParentsInTwoParentFamilies", "noOfKidsInTwoParentFamilies", "noOfIndividualsInTwoParentFamilies", \
"noOfSingleParentFamilies", "noOfParentsInSingleParentFamilies", "noOfKidsInSingleParentFamilies", "noOfIndividualsInSingleParentFamilies", \
"noOfZeroParentFamilies", "noOfParentsInZeroParentFamilies", "noOfKidsInZeroParentFamilies", "noOfIndividualsInZeroParentFamilies", \
"noOfTotalMendelErrors", \
"noOfMendelErrorsPerLocusPerNuclearFamily", "noOfMendelErrorsPerNuclearFamily"]
writer.writeHeader(header)
for row in reader:
meanMendelError = float(row[meanMendelErrorIndex])
noOfLoci = int(row[noOfLociIndex])
sumOfMendelError = int(row[sumOfMendelErrorIndex])
noOfNuclearFamilies = twoParentFamilyCountData.noOfFamilies
if noOfNuclearFamilies > 0:
noOfMendelErrorsPerLocusPerNuclearFamily = meanMendelError / float(
noOfNuclearFamilies)
noOfMendelErrorsPerNuclearFamily = sumOfMendelError / float(
noOfNuclearFamilies)
else:
noOfMendelErrorsPerLocusPerNuclearFamily = -1
noOfMendelErrorsPerNuclearFamily = -1
data_row = [row[0], noOfLoci, \
noOfNuclearFamilies, twoParentFamilyCountData.noOfParents, twoParentFamilyCountData.noOfKids, \
twoParentFamilyCountData.noOfIndividuals,\
singleParentFamilyCountData.noOfFamilies, singleParentFamilyCountData.noOfParents, singleParentFamilyCountData.noOfKids,\
singleParentFamilyCountData.noOfIndividuals,\
zeroParentFamilyCountData.noOfFamilies, zeroParentFamilyCountData.noOfParents, zeroParentFamilyCountData.noOfKids,\
zeroParentFamilyCountData.noOfIndividuals,\
sumOfMendelError, \
noOfMendelErrorsPerLocusPerNuclearFamily,noOfMendelErrorsPerNuclearFamily ]
writer.writerow(data_row)
plinkPedigreeFile.close()
reader.close()
writer.close()
def setup(self, **keywords):
"""
2012.10.15
run before anything is run
"""
AbstractMatrixFileWalker.setup(self, **keywords)
#self.writer = BeagleGenotypeFile(inputFname=self.outputFname, openMode='w')
#read in the IBD check result
self.ibdData = SNP.readAdjacencyListDataIntoMatrix(inputFname=self.pedigreeKinshipFilePath, \
rowIDHeader=None, colIDHeader=None, \
rowIDIndex=0, colIDIndex=1, \
dataHeader=None, dataIndex=2, hasHeader=False)
#. read in the alignment coverage data
alignmentCoverageFile = MatrixFile(inputFname=self.individualAlignmentCoverageFname)
alignmentCoverageFile.constructColName2IndexFromHeader()
alignmentReadGroup2coverageLs = alignmentCoverageFile.constructDictionary(keyColumnIndexList=[0], valueColumnIndexList=[1])
alignmentCoverageFile.close()
sys.stderr.write("Reading in all samples from %s VCF input files ... \n"%(len(self.inputFnameLs)))
# read all the Beagle files
individualID2HaplotypeData = {}
for inputFname in self.inputFnameLs:
vcfFile = VCFFile(inputFname=inputFname)
#vcfFile.readInAllHaplotypes()
for individualID in vcfFile.getSampleIDList():
individualID2HaplotypeData[individualID] = None
#haplotypeList = vcfFile.getHaplotypeListOfOneSample(individualID)
#individualID2HaplotypeData[individualID] = PassingData(haplotypeList=haplotypeList,
# locusIDList=vcfFile.locusIDList)
# get all haplotypes , etc.
# get all sample IDs
sys.stderr.write("%s individuals total.\n"%(len(individualID2HaplotypeData)))
#. read in the pedigree or deduce it from Beagle Trio/Duo genotype file (columns)
#. construct individualID2pedigreeContext, context: familySize=1/2/3, familyPosition=1/2 (parent/child)
sys.stderr.write("Constructing individualID2pedigreeContext ...")
plinkPedigreeFile = PlinkPedigreeFile(inputFname=self.pedigreeFname)
pGraph = plinkPedigreeFile.pedigreeGraph
#shrink the graph to only individuals with data
pGraph = nx.subgraph(pGraph, individualID2HaplotypeData.keys())
cc_subgraph_list = nx.connected_component_subgraphs(pGraph.to_undirected())
individualID2familyContext = {}
outDegreeContainer = NumberContainer(minValue=0)
familySizeContainer = NumberContainer(minValue=0)
individualCoverageContainer = NumberContainer(minValue=0)
familyCoverageContainer = NumberContainer(minValue=0)
for cc_subgraph in cc_subgraph_list:
familySize= len(cc_subgraph)
familySizeContainer.addOneValue(familySize)
familyCoverage = 0
for n in cc_subgraph: #assuming each family is a two-generation trio/nuclear family
individualCoverage = self.getIndividualCoverage(individualID=n, alignmentReadGroup2coverageLs=alignmentReadGroup2coverageLs)
individualCoverage = float(individualCoverage)
individualCoverageContainer.addOneValue(individualCoverage)
familyCoverage += individualCoverage
in_degree = pGraph.in_degree(n)
out_degree = pGraph.out_degree(n)
outDegreeContainer.addOneValue(out_degree)
familyContext = PassingData(familySize=familySize, in_degree=in_degree, out_degree=out_degree, \
individualCoverage=individualCoverage,\
familyCoverage=None)
if n not in individualID2familyContext:
individualID2familyContext[n] = familyContext
else:
sys.stderr.write("Node %s already in individualID2familyContext.\n"%(n))
familyCoverageContainer.addOneValue(familyCoverage)
#set the family coverage for each member, used in weighing the individual. better covered family => better haplotype
for n in cc_subgraph:
individualID2familyContext[n].familyCoverage = familyCoverage
plinkPedigreeFile.close()
sys.stderr.write("%s individuals.\n"%(len(individualID2familyContext)))
# weigh each unique individual based on its sequencing coverage + no of offspring => probability mass for each individual
sys.stderr.write("Weighing each individual , assigning probability mass ...")
individualID2probabilityMass = {}
for individualID, familyContext in individualID2familyContext.iteritems():
outDegreeQuotient = outDegreeContainer.normalizeValue(familyContext.familySize)
individualCoverageQuotient = individualCoverageContainer.normalizeValue(familyContext.individualCoverage)
#familyCoverageQuotient = familyCoverageContainer.normalizeValue(familyContext.familyCoverage)
importanceScore = outDegreeQuotient + individualCoverageQuotient
representativeImportanceScore = importanceScore
individualID2probabilityMass[individualID] = representativeImportanceScore
sys.stderr.write(" %s IDs with probability mass assigned.\n"%(len(individualID2probabilityMass)))
self.individualID2probabilityMass = individualID2probabilityMass
self.individualID2HaplotypeData = individualID2HaplotypeData
