def getAlleleCount(bamfile, snpfile, outfile):
brcparams = Box()
brcparams.f = ref
brcparams.w = 0
brcparams.l = snpfile
brcparams[''] = bamfile
cmd = '{bamrc} {args} > {outfile!r}'.format(
bamrc = bamrc, args = cmdargs(brcparams, equal = ' '), outfile = outfile + '.tmp')
runcmd(cmd)
# reformated output to desired format
reader = TsvReader(outfile + '.tmp', cnames = False)
snper = TsvReader(snpfile, cnames = False)
#chr1 564773 C 14 =:0:0.00:0.00:0.00:0:0:0.00:0.00:0.00:0:0.00:0.00:0.00 A:0:0.00:0.00:0.00:0:0:0.00:0.00:0.00:0:0.00:0.00:0.00 C:14:... G:0:... T:0:... N:0:...
writer = TsvWriter(outfile)
writer.cnames = ['Chrm', 'pos', 'A', 'C', 'G', 'T', 'Total', 'refCount', 'mutCount']
for r in reader:
while True:
try:
snp = next(snper)
except StopIteration:
break
# use the end position, in case it's 0-based
if snp[0] == r[0] and snp[2] == r[1]:
counts = dict(
A = r[5].split(':', 2)[1],
C = r[6].split(':', 2)[1],
G = r[7].split(':', 2)[1],
T = r[8].split(':', 2)[1]
)
rec = TsvRecord()
rec.Chrm = r[0]
rec.pos = r[1]
rec.Total = r[3]
rec.A = counts['A']
rec.C = counts['C']
rec.G = counts['G']
rec.T = counts['T']
# if reference allele is unknown, assuming all are ref alleles
rec.refCount = counts.get(snp[6].upper(), r[3])
# if mut allele is unknown, assuming no mutations happened
rec.mutCount = counts.get(snp[7].upper(), 0)
writer.write(rec)
# go to next snp
break
else:
# go to next r
continue
writer.close()
def main(opts):
"""Main function"""
org_tfgenes = read_tfgenes(opts.origin)
add_tfgenes = read_tfgenes(opts.addition)
writer = TsvWriter(opts.outfile)
logger.info('Writing the union set to %s ...', opts.outfile)
for gene, tfs in org_tfgenes.items():
for tf in (tfs | add_tfgenes.pop(gene, set())):
writer.write([tf, gene])
for gene, tfs in add_tfgenes.items():
for tf in tfs:
writer.write([tf, gene])
writer.close()
logger.info('Done.')
S1 S2 .. Sn
G1 ...
G2 ...
"""
expreader = TsvReader(expfile)
expdata = [r for r in expreader if r[0] in genes or r[0] in tfs]
expreader.close()
datawriter = TsvWriter(outdata)
for i, cname in enumerate(expreader.cnames):
if i == 0:
# genes + tfs
datawriter.cnames = [r[0] for r in expdata]
datawriter.writeHead()
else:
datawriter.write([cname] + [r[i] for r in expdata])
datawriter.close()
del expdata
genes = [g for g in genes if g in datawriter.cnames]
tfs = [g for g in tfs if g in datawriter.cnames]
genetfs = {g: [tf for tf in gtfs if tf in tfs] for g, gtfs in genetfs.items() if g in genes}
# save the group file
# mutfile
"""
S1 S2 .. Sn
M1 ... (0/1/2/NA)
M2 ...
"""
mutreader = TsvReader(mutfile)
mutdata = [r for r in mutreader if r[0] in mutgenes]
reader = TsvReader(infile, cnames=False)
allsnps = set(reader.dump(0))
reader.rewind()
allgenes = set(reader.dump(1))
reader.close()
# assign a probability to each snp
nsnps = len(allsnps)
ngenes = len(allgenes)
snp_probs = dict(zip(allsnps, random.choices(range(ngenes * snppergene),
k=nsnps)))
genebed = TsvWriter(genefile)
snpbed = TsvWriter(snpfile)
geneperchr = math.ceil(float(ngenes) / float(nchr))
for i, gene in enumerate(allgenes):
chrname = 'chr' + str(int(i % nchr) + 1)
start = (int(i / nchr) + 1) * dist
end = start + 1
first_snp_pos = int(start - dist/2.0 - snppergene)
snps = (snp for snp in snp_probs
if i * snppergene <= snp_probs[snp] < (i+1)*snppergene)
genebed.write([chrname, start, end, gene, 0, '+'])
for j, snp in enumerate(snps):
snppos = first_snp_pos + j
snpbed.write([chrname, snppos, snppos, snp, 0, '+'])
genebed.close()
snpbed.close()
for s in samples:
tfamWriter.write([s, s, '0', '0', 'other', '-9'])
else:
for s in samples:
tfamWriter.write([
metadata[s].FID if s in metadata and 'FID' in metadata[s] else s,
s, (metadata[s].PID or '0')
if s in metadata and 'PID' in metadata[s] else '0',
(metadata[s].MID or '0')
if s in metadata and 'MID' in metadata[s] else '0',
(metadata[s].Sex or 'other')
if s in metadata and 'Sex' in metadata[s] else 'other',
(metadata[s].Pheno or '-9')
if s in metadata and 'Pheno' in metadata[s] else '-9'
])
tfamWriter.close()
def getCompondGT(gt, ref, alt):
compGTs = {
"0": ref + ' ' + ref,
"1": ref + ' ' + alt,
"2": alt + ' ' + alt
}
return compGTs.get(gt, '0 0')
logger.info('Writing tped file ...')
tpedWriter = TsvWriter(tpedfile)
for r in inreader:
(chrom, pos, _, ref, alt) = r[0].split('_')
indata1 = TsvReader(infile1, **inopts1) indata2 = TsvReader(infile2, **inopts2) cnames1 = indata1.meta if not rnames1 else indata1.meta[1:] cnames2 = indata2.meta if not rnames2 else indata2.meta[1:] paired = list(set(cnames1) & set(cnames2)) cnames1 = cnames2 = paired if rnames1: cnames1 = [indata1.meta[0]] + cnames1 if rnames2: cnames2 = [indata2.meta[0]] + cnames2 cindex1 = [indata1.meta.index(c) for c in cnames1] cindex2 = [indata2.meta.index(c) for c in cnames2] outdata1 = TsvWriter(outfile1) outdata2 = TsvWriter(outfile2) outdata1.meta = cnames1 outdata2.meta = cnames2 outdata1.writeHead() outdata2.writeHead() for r1 in indata1: outdata1.write(r1[i] for i in cindex1) outdata1.close() for r2 in indata2: outdata2.write(r2[i] for i in cindex2) outdata2.close()
from bioprocs.utils.tsvio2 import TsvReader, TsvWriter
infile = {{i.infile | quote}}
outfile = {{o.outfile | quote}}
inopts = {{args.inopts | repr}}
infmt = {{args.infmt | quote}}
cutoff = {{args.cutoff | repr}}
degrees = defaultdict(lambda: 0)
if infmt.startswith('pair'):
reader = TsvReader(infile, **inopts)
for r in reader:
if cutoff:
try:
score = float(r[2])
except TypeError:
raise TypeError(
'The 3rd column should be a score for apply the cutoff.')
if score < cutoff:
continue
degrees[r[0]] += 1
degrees[r[1]] += 1
writer = TsvWriter(outfile)
for node in sorted(degrees.keys(), key=lambda x: degrees[x], reverse=True):
if infmt.endswith('complete'):
writer.write([node, int(int(degrees[node]) / 2)])
else:
writer.write([node, degrees[node]])
writer.close()
else:
raise ValueError('Input format other than "pair" not supported yet.')