def target():
while 1:
try:
res = qin.get(PIPING, 1)
except queue.Empty:
if not PIPING:
break
else:
continue
qname, sname = res['query']['name'], res['subject']['name']
start, end = res['query']['start'], res['query']['end']
alignments = []
max_match = (options.MIN_IDENTITY, None)
if subj[sname].type == 'nucl':
subject = translate(subj[sname])
else:
subject = subj[sname]
while qname:
try:
o = orfs[qname]
break
except KeyError:
qname = qname[:-1]
if not qname:
qin.task_done()
continue
for orf in o:
if in_range(orf, start, end, 0):
orf = orf[:-3]
query = translate(orf)
options.debug("Aligning %33s v. %33s." % (qname, sname))
alignment = align(subject.seq, query.seq)
alignments.append((orf, sname, alignment))
for orf, refname, aln in alignments:
hitlen = aln['sublength']
region = orf[-3 * hitlen:]
identity = float(aln['identities']) / aln['length']
if identity >= max_match[0]:
max_match = (identity, (region, sname, aln))
if max_match[1]:
seq, name, _ = max_match[1]
odl = subject.defline.split('[')[0].strip()
src = seq.original.name
start, end, strand = seq.start, seq.end, seq.step
defline = '%s[source=%s] [start=%d] [end=%d] [strand=%d]' % \
(odl + (' ' if odl else ''), src, start, end, strand)
new = Sequence(name.strip(), seq.seq, defline=defline,
original=seq.original, type=seq.type,
start=seq.start, end=seq.end, step=seq.step)
qout.put(new)
qin.task_done()
def run_predict():
while 1:
try:
strainf = q.get(False)
except queue.Empty:
break
strain = strainf.split(sep)[-1]
pos = strain.rfind(".")
if pos > 1 or (pos == 1 and strain[0] != "."):
strain = strain[:pos]
options.debug("Predicting for %s." % strain)
try:
genepredict.run(infile, strainf, strain, filenames)
except RuntimeError:
pass
q.task_done()
def GeneFromBLAST(db, sequences, pref, names):
'''
BLASTs database against sequences, and for those results that pass the
length and percent identity requirements, attempt to locate the full gene
that corresponds to that BLAST hit. Genes that are found are saved in the
subdirectory sequences under the given directory, divided depending on
whether the sequnece is amino acid or nucleotide.
'''
PIPING = True
wd = options.DIRECTORY + 'sequences' + sep
for d in [options.DIRECTORY, wd]:
try:
mkdir(d)
except OSError:
pass
subj = dict((s.name, s) for s in io.open(db, 'r'))
options.debug("Database sequences loaded from file %s." % db)
try:
orfs = dict((s.name, [orf for orf in ORFGenerator(s)])
for s in io.open(sequences, 'r'))
options.debug("ORFs loaded from file %s." % sequences)
except IOError:
options.debug("No file \"" + sequences + ",\" skipping.")
return
def target():
while 1:
try:
res = qin.get(PIPING, 1)
except queue.Empty:
if not PIPING:
break
else:
continue
qname, sname = res['query']['name'], res['subject']['name']
start, end = res['query']['start'], res['query']['end']
alignments = []
max_match = (options.MIN_IDENTITY, None)
if subj[sname].type == 'nucl':
subject = translate(subj[sname])
else:
subject = subj[sname]
while qname:
try:
o = orfs[qname]
break
except KeyError:
qname = qname[:-1]
if not qname:
qin.task_done()
continue
for orf in o:
if in_range(orf, start, end, 0):
orf = orf[:-3]
query = translate(orf)
options.debug("Aligning %33s v. %33s." % (qname, sname))
alignment = align(subject.seq, query.seq)
alignments.append((orf, sname, alignment))
for orf, refname, aln in alignments:
hitlen = aln['sublength']
region = orf[-3 * hitlen:]
identity = float(aln['identities']) / aln['length']
if identity >= max_match[0]:
max_match = (identity, (region, sname, aln))
if max_match[1]:
seq, name, _ = max_match[1]
odl = subject.defline.split('[')[0].strip()
src = seq.original.name
start, end, strand = seq.start, seq.end, seq.step
defline = '%s[source=%s] [start=%d] [end=%d] [strand=%d]' % \
(odl + (' ' if odl else ''), src, start, end, strand)
new = Sequence(name.strip(), seq.seq, defline=defline,
original=seq.original, type=seq.type,
start=seq.start, end=seq.end, step=seq.step)
qout.put(new)
qin.task_done()
def in_range(seq, start, end, frame):
ss, se = sorted((seq.start, seq.end))
os, oe = sorted((start, end))
frame = int(frame)
return (ss < oe and se > os and (se % 3 == oe % 3 or ss % 3 == oe % 3) )
qout = queue.Queue()
qin = ThreadQueue(target)
blastopts = {
'evalue': options.MAX_EVALUE,
'num_threads': options.NUM_THREADS
}
for res in BLAST.run(db, sequences, **blastopts):
if float(res['expect']) > options.MAX_EVALUE:
continue
sbjl = len(subj[res['subject']['name']])
ident = float(res['identities'].split('(')[1][:-2]) / 100
lerr = float(res['subject']['length']) / sbjl
if ident >= options.MIN_IDENTITY:
if lerr >= (1.0 - options.LENGTH_ERR):
qin.put(res)
PIPING = False
options.debug("BLAST done.")
target()
qin.join()
options.debug("Done Aligning sequences.")
options.debug("Now writing sequences (%d)." % qout.qsize())
seqs = {}
nuc_file = io.open(wd + pref + '.fasta', 'w')
count = 0
while 1:
try:
seq = qout.get(False)
if seq.seq not in seqs:
seqs[seq.seq] = set()
seqs[seq.seq].add(seq)
nuc_file.write(seq)
count += 1
options.debug("Wrote %s (%d)." % (seq.name, count));
except queue.Empty:
break
nuc_file.close()
options.debug("Done Aligning sequences.")
gh = io.open(wd + pref + '.gff3', 'w')
names.append(wd + pref + '.fasta')
for id in seqs:
gh.write(ann(seqs[id].copy().pop(), pref, 'gene',
homologs=','.join(s.name for s in seqs[id])))
gh.close()
