def convertOpticalMaps(opticalMapFile, outputPfx):
opMapFileOut = '%s.opt'%outputPfx
msg = '\n'+'*'*50 + \
'\nReading Optical Map File %s\n'%opticalMapFile + \
'*'*50 + '\n'
sys.stderr.write(msg)
opMapList = make_opt.readMapDataSchwartz(opticalMapFile)
enzymeSet = set(om.enzyme for om in opMapList)
if len(enzymeSet) > 1:
raise RuntimeError('Different enzymes used in the input optical map set!')
enzyme = opMapList[0].enzyme
msg = '\n'+'*'*50 +\
'\nConverting Optical Map to SOMA Format\n' +\
'*'*50 + '\n'
sys.stderr.write(msg)
# Optical maps for chromosomes
# Remove all white space from restriction map names
for opMap in opMapList:
opMap.mapId = ''.join(opMap.mapId.split())
SOMAMap.writeMaps(opMapList, opMapFileOut)
result = { 'enzyme' : enzyme,
'opMapList' : opMapList,
'opticalMapFile' : opMapFileOut}
return result
def postProcess(xmlFile, opticalMapFile, contigMapFile, outputPfx):
# Parse results
print '\n'+'*'*50
print 'Parsing SOMA OUTPUT...'
print '*'*50 + '\n'
pickleFileAll = '%s.matchList.all.pickle'%outputPfx
pickleFileSig = '%s.matchList.sig.pickle'%outputPfx
pickleFileSigUnique = '%s.matchList.sig.unique.pickle'%outputPfx
# Parse Match Results. Write Pickle Files
ml = parseSomaMatch.parseMatchFileXML(xmlFile)
significanceTest.runSignificanceTest(ml, contigMapFile, opticalMapFile, numThreads=numThreads)
# Select significant results
pvalCutoff = 0.05
sigMatches = [mr for mr in ml if mr.pval <= pvalCutoff]
sigMatchDict = parseSomaMatch.collectMatchResultsByContig(sigMatches)
sigUniqueMatches = [matches[0] for contigId, matches in sigMatchDict.iteritems() if len(matches)==1]
sigUniqueMatchDict = parseSomaMatch.collectMatchResultsByContig(sigUniqueMatches)
sys.stdout.write('Found %i significant matches (%i bp)\n'%(len(sigMatches), sum(mr.cAlignedBases for mr in sigMatches)))
sys.stdout.write('Found %i unique significant matches (%i bp)\n'%(len(sigUniqueMatches), sum(mr.cAlignedBases for mr in sigUniqueMatches)))
# Pickle the matchResults
cPickle.dump(ml, open(pickleFileAll, 'w'))
cPickle.dump(sigMatches, open(pickleFileSig, 'w'))
cPickle.dump(sigUniqueMatches, open(pickleFileSigUnique, 'w'))
infoFileOut = '%s.info'%outputPfx
parseSomaMatch.writeInfoFile2(ml, infoFileOut)
# Summarize alignment status for contigs in the silicoFile
contigMapDict = SOMAMap.readMaps(contigMapFile)
opMapDict= SOMAMap.readMaps(opticalMapFile)
summarizeContigStatus.summarizeContigStatus(outputPfx, sigMatchDict, contigMapDict)
# Print all of the alignments to a textFile
fout = open('%s.SigUniqueAlignments.txt'%outputPfx, 'w')
parseSomaMatch.printAlignments(sigUniqueMatches, fout)
fout.close()
fout = open('%s.AllSigAlignments.txt'%outputPfx, 'w')
parseSomaMatch.printAlignments(sigMatches, fout)
fout.close()
# Create scaffolds
print '\n'+'*'*50
print 'Creating Scaffolds...'
print '*'*50 + '\n'
createScaffolds.createScaffolds(sigMatchDict, opMapDict, '%s.scaffold_sigMatches_withOverlaps.txt'%outputPfx, allowOverlaps=True)
createScaffolds.createScaffolds(sigMatchDict, opMapDict, '%s.scaffold_sigMatches_noOverlaps.txt'%outputPfx, allowOverlaps=False)
createScaffolds.createScaffolds(sigUniqueMatchDict, opMapDict, '%s.scaffold_sigUniqueMatches_withOverlaps.txt'%outputPfx, allowOverlaps=True)
createScaffolds.createScaffolds(sigUniqueMatchDict, opMapDict, '%s.scaffold_sigUniqueMatches_noOverlaps.txt'%outputPfx, allowOverlaps=False)
def addFragsFromMap(self, mapFileName):
mapDict = SOMAMap.readMaps(open(mapFileName))
for mapId, mapObj in mapDict.iteritems():
frags = mapObj.frags
if not frags:
continue
self.addFrags(frags)
if len(frags) > 2:
self.addInteriorFrags(frags[1:-1])
