def __calculateResults(self, windowSizes, numWindows, genomeDir, queueIn,
queueOut):
while True:
genomeId = queueIn.get(block=True, timeout=None)
if genomeId == None:
break
seqs = readGenomicSeqsFromFasta(
os.path.join(genomeDir, genomeId, genomeId + '.fna'))
# calculate GC of genome
numericGenome = self.__createNumericGenome(seqs)
counts = np.bincount(numericGenome)
gc = counts[0]
totalBases = gc + counts[1]
meanGC = float(gc) / totalBases
fout = open('./deltaGC/' + genomeId + '.tsv', 'w')
fout.write('# Mean GC = ' + str(meanGC) + '\n')
# calculate GC distribution for different window sizes
for windowSize in windowSizes:
endWindowPos = len(numericGenome) - windowSize
if endWindowPos <= 0:
# This might occur for the largest window sizes and smallest genomes
break
requiredBasePairs = 0.9 * windowSize
deltaGCs = []
while len(deltaGCs) != numWindows:
# pick random window
startWindow = randint(0, endWindowPos)
# calculate GC
counts = np.bincount(
numericGenome[startWindow:(startWindow + windowSize)])
gc = counts[0]
totalBases = gc + counts[1]
if totalBases < requiredBasePairs:
# there are N's in the window so skip it
continue
gcPer = float(gc) / totalBases
deltaGCs.append(gcPer - meanGC)
fout.write('Windows Size = ' + str(windowSize) + '\n')
fout.write(','.join(map(str, deltaGCs)) + '\n')
fout.close()
queueOut.put(genomeId)
def __calculateResults(self, windowSizes, numWindows, genomeDir, queueIn,
queueOut):
while True:
genomeId = queueIn.get(block=True, timeout=None)
if genomeId == None:
break
start = time.time()
seqs = readGenomicSeqsFromFasta(
os.path.join(genomeDir, genomeId, genomeId + '.fna'))
genomeScaffold = 'NNNN'.join(seqs.values())
# calculate tetranucleotide signature of genome
gsCalculator = GenomicSignatures(4)
genomeSig = gsCalculator.seqSignature(genomeScaffold)
fout = open('./deltaTD/' + genomeId + '.tsv', 'w')
fout.write('# Tetra signature = ' + str(genomeSig) + '\n')
fout.close()
sys.exit()
# calculate tetranucleotide distance distribution for different window sizes
startW = time.time()
for windowSize in windowSizes:
endWindowPos = len(genomeScaffold) - windowSize
if endWindowPos <= 0:
# This might occur for the largest window sizes and smallest genomes
break
deltaTDs = []
while len(deltaTDs) != numWindows:
# pick random window
startWindow = randint(0, endWindowPos)
windowSig = gsCalculator.seqSignature(
genomeScaffold[startWindow:(startWindow + windowSize)])
dist = gsCalculator.distance(genomeSig, windowSig)
deltaTDs.append(dist)
fout.write('Windows Size = ' + str(windowSize) + '\n')
fout.write(','.join(map(str, deltaTDs)) + '\n')
fout.close()
endW = time.time()
print endW - startW
queueOut.put(genomeId)
end = time.time()
print end - start
def __calculateResults(self, windowSizes, numWindows, genomeDir, queueIn, queueOut):
while True:
genomeId = queueIn.get(block=True, timeout=None)
if genomeId == None:
break
seqs = readGenomicSeqsFromFasta(os.path.join(genomeDir, genomeId, genomeId + '.fna'))
# calculate GC of genome
numericGenome = self.__createNumericGenome(seqs)
counts = np.bincount(numericGenome)
gc = counts[0]
totalBases = gc + counts[1]
meanGC = float(gc) / totalBases
fout = open('./deltaGC/' + genomeId + '.tsv', 'w')
fout.write('# Mean GC = ' + str(meanGC) + '\n')
# calculate GC distribution for different window sizes
for windowSize in windowSizes:
endWindowPos = len(numericGenome) - windowSize
if endWindowPos <= 0:
# This might occur for the largest window sizes and smallest genomes
break
requiredBasePairs = 0.9*windowSize
deltaGCs = []
while len(deltaGCs) != numWindows:
# pick random window
startWindow = randint(0, endWindowPos)
# calculate GC
counts = np.bincount(numericGenome[startWindow:(startWindow+windowSize)])
gc = counts[0]
totalBases = gc + counts[1]
if totalBases < requiredBasePairs:
# there are N's in the window so skip it
continue
gcPer = float(gc) / totalBases
deltaGCs.append(gcPer - meanGC)
fout.write('Windows Size = ' + str(windowSize) + '\n')
fout.write(','.join(map(str, deltaGCs)) + '\n')
fout.close()
queueOut.put(genomeId)
def __calculateResults(self, windowSizes, numWindows, genomeDir, queueIn, queueOut):
while True:
genomeId = queueIn.get(block=True, timeout=None)
if genomeId == None:
break
start = time.time()
seqs = readGenomicSeqsFromFasta(os.path.join(genomeDir, genomeId, genomeId + '.fna'))
genomeScaffold = 'NNNN'.join(seqs.values())
# calculate tetranucleotide signature of genome
gsCalculator = GenomicSignatures(4)
genomeSig = gsCalculator.seqSignature(genomeScaffold)
fout = open('./deltaTD/' + genomeId + '.tsv', 'w')
fout.write('# Tetra signature = ' + str(genomeSig) + '\n')
fout.close()
sys.exit()
# calculate tetranucleotide distance distribution for different window sizes
startW = time.time()
for windowSize in windowSizes:
endWindowPos = len(genomeScaffold) - windowSize
if endWindowPos <= 0:
# This might occur for the largest window sizes and smallest genomes
break
deltaTDs = []
while len(deltaTDs) != numWindows:
# pick random window
startWindow = randint(0, endWindowPos)
windowSig = gsCalculator.seqSignature(genomeScaffold[startWindow:(startWindow+windowSize)])
dist = gsCalculator.distance(genomeSig, windowSig)
deltaTDs.append(dist)
fout.write('Windows Size = ' + str(windowSize) + '\n')
fout.write(','.join(map(str, deltaTDs)) + '\n')
fout.close()
endW = time.time()
print endW - startW
queueOut.put(genomeId)
end = time.time()
print end - start
def __calculateResults(self, windowSizes, numWindows, genomeDir, queueIn, queueOut):
while True:
genomeId = queueIn.get(block=True, timeout=None)
if genomeId == None:
break
seqs = readGenomicSeqsFromFasta(os.path.join(genomeDir, genomeId, genomeId + '.fna'))
# for simplicity, create a single scaffold from all sequences
genomeFile = os.path.join('./deltaCD/genomes', genomeId + '.single_scaffold.fna')
genomeScaffold = 'NNNNNNNNNN'.join(list(seqs.values())).upper()
fout = open(genomeFile, 'w')
fout.write('>' + genomeId + '\n')
fout.write(genomeScaffold)
fout.close()
# run prodigal on genome
ntFile = os.path.join('./deltaCD/prodigal', genomeId + '.genes.fna')
gffFile = os.path.join('./deltaCD/prodigal', genomeId + '.gff')
cmd = ('prodigal -q -c -m -f gff -d %s -i %s > %s' % (ntFile, genomeFile, gffFile))
os.system(cmd)
# calculate mean coding density of genome
numericScaffold = self.__createNumericScaffold(genomeScaffold)
prodigalParser = ProdigalGeneFeatureParser(gffFile)
codingBases = prodigalParser.codingBases(genomeId)
counts = np.bincount(numericScaffold)
totalBases = counts[0]
meanCD = float(codingBases) / totalBases
fout = open('./deltaCD/' + genomeId + '.tsv', 'w')
fout.write('# Mean CD = ' + str(meanCD) + '\n')
# calculate coding density distribution for different window sizes
for windowSize in windowSizes:
endWindowPos = len(genomeScaffold) - windowSize
if endWindowPos <= 0:
# This might occur for the largest window sizes and smallest genomes
break
deltaCDs = []
while len(deltaCDs) != numWindows:
# pick random window
startWindow = randint(0, endWindowPos)
# calculate coding density
codingBases = prodigalParser.codingBases(genomeId, startWindow, startWindow+windowSize)
counts = np.bincount(numericScaffold[startWindow:(startWindow+windowSize)])
totalBases = counts[0]
if totalBases != windowSize:
# there are N's in the window so skip it
continue
cdPer = float(codingBases) / totalBases
deltaCDs.append(cdPer - meanCD)
fout.write('Windows Size = ' + str(windowSize) + '\n')
fout.write(','.join(map(str, deltaCDs)) + '\n')
fout.close()
queueOut.put(genomeId)
def __calculateResults(self, windowSizes, numWindows, genomeDir, queueIn, queueOut):
while True:
genomeId = queueIn.get(block=True, timeout=None)
if genomeId == None:
break
seqs = readGenomicSeqsFromFasta(os.path.join(genomeDir, genomeId, genomeId + '.fna'))
# for simplicity, create a single scaffold from all sequences
genomeFile = os.path.join('./deltaCD/genomes', genomeId + '.single_scaffold.fna')
genomeScaffold = 'NNNNNNNNNN'.join(seqs.values()).upper()
fout = open(genomeFile, 'w')
fout.write('>' + genomeId + '\n')
fout.write(genomeScaffold)
fout.close()
# run prodigal on genome
ntFile = os.path.join('./deltaCD/prodigal', genomeId + '.genes.fna')
gffFile = os.path.join('./deltaCD/prodigal', genomeId + '.gff')
cmd = ('prodigal -q -c -m -f gff -d %s -i %s > %s' % (ntFile, genomeFile, gffFile))
os.system(cmd)
# calculate mean coding density of genome
numericScaffold = self.__createNumericScaffold(genomeScaffold)
prodigalParser = ProdigalGeneFeatureParser(gffFile)
codingBases = prodigalParser.codingBases(genomeId)
counts = np.bincount(numericScaffold)
totalBases = counts[0]
meanCD = float(codingBases) / totalBases
fout = open('./deltaCD/' + genomeId + '.tsv', 'w')
fout.write('# Mean CD = ' + str(meanCD) + '\n')
# calculate coding density distribution for different window sizes
for windowSize in windowSizes:
endWindowPos = len(genomeScaffold) - windowSize
if endWindowPos <= 0:
# This might occur for the largest window sizes and smallest genomes
break
deltaCDs = []
while len(deltaCDs) != numWindows:
# pick random window
startWindow = randint(0, endWindowPos)
# calculate coding density
codingBases = prodigalParser.codingBases(genomeId, startWindow, startWindow+windowSize)
counts = np.bincount(numericScaffold[startWindow:(startWindow+windowSize)])
totalBases = counts[0]
if totalBases != windowSize:
# there are N's in the window so skip it
continue
cdPer = float(codingBases) / totalBases
deltaCDs.append(cdPer - meanCD)
fout.write('Windows Size = ' + str(windowSize) + '\n')
fout.write(','.join(map(str, deltaCDs)) + '\n')
fout.close()
queueOut.put(genomeId)