def generateMotifs(seqGroups, align, outputPrefix, transSeq=False,
extendAlphabet=False, clusterMotifs=False, protein=False, threads=2, stream=None):
from TAMO.MotifTools import Motif
ighvMotifs = []
if clusterMotifs and 'gene' in outputPrefix:
findMotifClusters(ighvMotifs, outputPrefix, stream=stream)
printto(stream, '\t\tPWMs, consensus and logos are being generated for {} motifs ... '.format(len(seqGroups)))
pwmFile = open(outputPrefix + '_pwm.txt', 'w')
consensusFile = open(outputPrefix + '_consensus.txt', 'w')
logosFolder = outputPrefix + '_logos'
if not os.path.exists(logosFolder):
os.makedirs(logosFolder)
# create the sequence alphabet: DNA or Protein
alphabet = createAlphabet(align, transSeq, extendAlphabet, protein)
groups = seqGroups.keys()
groups.sort()
for group in groups:
filename = os.path.join(logosFolder, group.replace('/', '') + '.png')
seqs = seqGroups[group]
m = generateMotif(seqs, group, alphabet, filename, align, transSeq, protein, outDir=logosFolder,
threads=threads, stream=stream)
if m is None:
# motif file found, no further work required
return
motifSeqs = m.instances
pwm = m.counts.normalize(pseudocounts=None) # {'A':0.6, 'C': 0.4, 'G': 0.4, 'T': 0.6}
consensusMax = str(m.consensus)
pwmFile.write('#{} {} sequences\n'.format(group, len(motifSeqs)))
pwmFile.write(str(pwm))
consensusFile.write('>{} max_count\n'.format(group))
consensusFile.write(consensusMax + '\n')
# print(str(m.anticonsensus)) # smallest values in the columns
if not transSeq and not align and not protein:
consensusIupac = str(m.degenerate_consensus)
# print(consensusIupac) # IUPAC ambiguous nucleotides
consensusFile.write('>{} degenerate\n'.format(group))
consensusFile.write(consensusIupac + '\n')
pwmFile.flush()
consensusFile.flush()
gc.collect()
if clusterMotifs and len(motifSeqs) > 10:
motif = Motif(map(lambda x: str(x), motifSeqs),
backgroundD={'A': 0.6, 'C': 0.4, 'G': 0.4, 'T': 0.6}, id=group)
motif.addpseudocounts(0.1)
ighvMotifs.append(motif)
pwmFile.close()
consensusFile.close()
gc.collect()
printto(stream, "\tPosition weight matrices are written to " + os.path.basename(outputPrefix + '_pwm.txt'))
printto(stream, "\tConsensus sequences are written to " + os.path.basename(outputPrefix + '_consensus.txt'))
if clusterMotifs:
findMotifClusters(ighvMotifs, outputPrefix, stream=stream)
