def filter_encompassing_chimeras(input_file, output_file, gene_file,
max_multimap=1,
multimap_cov_ratio=0.10,
max_isize=1000,
strand_pval=0.01,
keep_overlap=False):
logging.debug("Filtering chimeras")
logging.debug("Must have a read with <= %d multimaps" % (max_multimap))
logging.debug("Coverage to reads ratio >= %f" % (multimap_cov_ratio))
logging.debug("Insert size < %d" % (max_isize))
logging.debug("Strand balance p-value > %f" % (strand_pval))
# first perform basic filtering
tmpfile1 = make_temp(base_dir=os.path.dirname(output_file),
suffix='.bedpe')
fh = open(tmpfile1, "w")
for c in Chimera.parse(open(input_file)):
res = filter_multimapping(c, max_multimap=max_multimap,
multimap_cov_ratio=multimap_cov_ratio)
res = res and filter_insert_size(c, max_isize)
if not keep_overlap:
res = res and filter_overlapping(c)
res = res and filter_strand_balance(c, strand_pval)
if res:
print >>fh, '\t'.join(map(str, c.to_list()))
fh.close()
logging.debug("Building gene/genome index")
ggmap = build_gene_to_genome_map(open(gene_file))
logging.debug("Finding junction permiscuity")
juncmap5p, juncmap3p = collect_permiscuity_stats(tmpfile1, ggmap)
fh = open(output_file, "w")
for c in Chimera.parse(open(tmpfile1)):
frac5p, frac3p = calc_permiscuity(c, juncmap5p, juncmap3p, ggmap)
c.mate5p.frac = frac5p
c.mate3p.frac = frac3p
print >>fh, '\t'.join(map(str, c.to_list()))
fh.close()
# delete tmp files
os.remove(tmpfile1)
def filter_spanning_chimeras(input_file, output_file, gene_file,
mate_pval, max_isize):
'''
processes chimera isoforms and chooses the one with the
highest coverage and omits the rest
'''
# apply more filters
tmpfile = make_temp(os.path.dirname(output_file), suffix='.bedpe')
fh = open(tmpfile, "w")
for c in SpanningChimera.parse(open(input_file)):
res = filter_insert_size(c, max_isize)
if res:
print >>fh, '\t'.join(['\t'.join(map(str,c.to_list()))])
fh.close()
# choose best isoform from remaining isoforms
logging.debug("Building gene/genome index")
ggmap = build_gene_to_genome_map(open(gene_file))
logging.debug("Choosing highest coverage chimeras")
fh = open(output_file, "w")
for c in choose_highest_coverage_chimeras(tmpfile, ggmap):
print >>fh, '\t'.join(['\t'.join(map(str,c.to_list()))])
fh.close()
# remove temporary file
os.remove(tmpfile)
def filter_spanning_chimeras(input_file, output_file, gene_file, mate_pval,
max_isize):
'''
processes chimera isoforms and chooses the one with the
highest coverage and omits the rest
'''
# apply more filters
tmpfile = make_temp(os.path.dirname(output_file), suffix='.bedpe')
fh = open(tmpfile, "w")
for c in SpanningChimera.parse(open(input_file)):
res = filter_insert_size(c, max_isize)
if res:
print >> fh, '\t'.join(['\t'.join(map(str, c.to_list()))])
fh.close()
# choose best isoform from remaining isoforms
logging.debug("Building gene/genome index")
ggmap = build_gene_to_genome_map(open(gene_file))
logging.debug("Choosing highest coverage chimeras")
fh = open(output_file, "w")
for c in choose_highest_coverage_chimeras(tmpfile, ggmap):
print >> fh, '\t'.join(['\t'.join(map(str, c.to_list()))])
fh.close()
# remove temporary file
os.remove(tmpfile)
