def getIdentifiersConversionTableUsingGff3():
global altIdentifiers
if altIdentifiers:
return altIdentifiers
gm = getGenomeModelFromCache(taxId)
for protId in SpeciesCDSSource(taxId):
cds = CDSHelper(taxId, protId)
geneId = cds.getGeneId()
alts = gm.findEquivalentIdentifiers(geneId)
for i in alts:
altIdentifiers[i] = protId
altIdentifiers[geneId] = protId
def testSpecies(taxId):
paData = getSpeciesPaxdbData( taxId )
countFound = 0
countNotFound = 0
for protId in SpeciesCDSSource(taxId):
cds = CDSHelper( taxId=taxId, protId=protId )
geneId = cds.getGeneId()
if geneId in paData:
countFound += 1
else:
countNotFound += 1
print("Species: {} -> Found: {} ({:.3}%) Not found: {}".format(taxId, countFound, countFound/(countFound+countNotFound)*100, countNotFound))
return( countFound, countNotFound)
def processGenome(args, taxId):
alreadyProcessedGenes = {}
totalProteinsProcessed = 0
totalSkipped = 0
seqsForWriting=[]
recordsForWriting={}
gm = getGenomeModelFromCache( taxId )
for protId in SpeciesCDSSource(taxId):
cds = CDSHelper( taxId, protId )
totalProteinsProcessed += 1
#feature = gm.findFeatureById( protId )
geneId = cds.getGeneId()
#flanking3UTRRegionLengthNt = cds.flankingRegion3UtrLength()
feature = gm.findFeatureById( protId )
#feature = cds.getMatchingFeatureFromGenomeModel()
#print(feature)
strand = feature[1].data['strand']
if strand=='+':
otherFeature = gm.moleculeModels[ feature[0] ].find5PrimeFlankingRegion( feature[1] )
if otherFeature is None:
totalSkipped += 1
continue
assert( otherFeature['downstream-feature'].begin <= otherFeature['downstream-feature'].end)
flanking3UTRRegionLengthNt = otherFeature['curr-feature'].begin - otherFeature['downstream-feature'].end
threePrimeUTRCoords = (feature[1].begin-20, feature[1].begin+2, False) # include the first 3 nucleotides of the CDS
else:
otherFeature = gm.moleculeModels[ feature[0] ].find5PrimeFlankingRegion( feature[1] )
if otherFeature is None:
totalSkipped += 1
continue
assert( otherFeature['downstream-feature'].begin <= otherFeature['downstream-feature'].end)
flanking3UTRRegionLengthNt = otherFeature['downstream-feature'].begin - otherFeature['curr-feature'].end
threePrimeUTRCoords = (feature[1].end-3, feature[1].end+20, True) # include the first 3 nucleotides of the CDS
threePrimeUTR = gm.moleculeModels[ feature[0] ].getSequence( *threePrimeUTRCoords )
if flanking3UTRRegionLengthNt < -50:
print("Warning: found gene with apparent long overlap: {},{},{},{},{}".format( protId, geneId, strand, flanking3UTRRegionLengthNt, threePrimeUTR.seq ))
#totalSkipped += 1
#continue
if threePrimeUTR.seq[-2:] != 'TG':
print("Warning: skipping gene with start codon at the correct place: {},{},{},{},{}".format( protId, geneId, strand, flanking3UTRRegionLengthNt, threePrimeUTR.seq ))
totalSkipped += 1
continue
# All done - emit the output
#fout.write("{},{},{},{},{}".format( protId, geneId, strand, flanking3UTRRegionLengthNt, threePrimeUTR.seq ))
recordsForWriting[protId] = (geneId, strand, flanking3UTRRegionLengthNt, threePrimeUTR.seq )
seqsForWriting.append( SeqRecord( Seq(threePrimeUTR.seq[:-3], NucleotideAlphabet), id=protId) )
aSD = calculateaSDEnergies( seqsForWriting, args, taxId )
print(len(aSD))
with open( outputData.format(taxId), 'wt') as fout:
for protId, record in recordsForWriting.items():
aSDval = aSD.get(protId, None)
vals = (protId,) + record + (aSDval,)
fout.write("{},{},{},{},{},{}\n".format( *vals ))
print("Processed {} coding sequences for taxid {}".format( totalProteinsProcessed, taxId ))
print("Skipped {} coding sequences".format( totalSkipped ))
