def main_validate(args, stdout, stderr) :
def mean(x) :
return sum(x) * 1. / len(x)
if args.outDir is None :
args.outDir = "."
for inputFile in args.input :
try :
stderr.write("Processing file " + inputFile + "\n")
aln = AlignIO.read(inputFile, "fasta")
if args.N_seqs is None or len(aln) <= args.N_seqs :
seqScores = pyalign.sequenceConservation(aln)
seqsKept = [seq for (seq, score) in zip(aln, seqScores) if score >= args.seqcons]
cleanAln = MultipleSeqAlignment(seqsKept)
alnCons = mean(pyalign.conservationProfile(cleanAln))
outFile = os.path.join(args.outDir, inputFile)
if (len(cleanAln) >= args.n_seqs) and (alnCons >= args.conservation) :
with open(outFile, "w") as fo :
for seq in cleanAln :
fo.write(">" + seq.description + "\n")
fo.write(str(seq.seq) + "\n")
else :
if args.outDir == "." :
os.remove(inputFile)
else :
if args.outDir == "." :
os.remove(inputFile)
except :
stderr.write("Problem with " + inputFile + "\n")
def main_consensus(args, stdout, stderr) :
stderr.write("Note that positions with only gaps are removed before "
"calculations\n")
consensus = dict()
profiles = dict()
i = 0
total = str(len(args.input))
for fastaFile in args.input :
i += 1
stderr.write("Processing file " + str(i) + "/" + total + " ")
try :
aln = pyalign.AlignIO.read(fastaFile, "fasta")
stderr.write("- " + str(len(aln)) + " sequences ")
stderr.write(".")
aln = pyalign.ungapAln(aln)["ungappedAln"]
stderr.write(".")
k = os.path.basename(fastaFile)
assert not k in consensus
consensus[k] = pyalign.makeConsensus(aln)
stderr.write(".")
stdout.write(">" + k + "\n")
stdout.write(consensus[k] + "\n")
profiles[k] = pyalign.conservationProfile(aln)
stderr.write(".\n")
except ValueError :
msg = "Problem with " + fastaFile + "\n"
stderr.write(msg)
keys = list(consensus.keys())
if args.profiles is not None :
stderr.write("Writing profiles\n")
with open(args.profiles, "w") as fo :
for k in keys :
fo.write("\t".join([k] + [str(x) for x in profiles[k]]) + "\n")
if args.conservation is not None :
stderr.write("Writing conservation values\n")
def mean(x) :
return sum(x) * 1. / len(x)
with open(args.conservation, "w") as fo :
for k in keys :
fo.write(k + "\t" + str(mean(profiles[k])) + "\n")
