def annotate_fusion(ref_f, input_f, output_f):
"""
Align fusion juncrions to gene annotations
"""
print('Start to annotate fusion junctions...')
genes, gene_info = parse_ref1(ref_f) # gene annotations
fusions, fusion_index = parse_bed(input_f) # fusion junctions
total = set()
with open(output_f, 'w') as outf:
for chrom in genes:
# overlap gene annotations with fusion juncrions
result = Interval.overlapwith(genes[chrom].interval,
fusions[chrom])
for itl in result:
# extract gene annotations
iso = list(filter(lambda x: x.startswith('iso'), itl[2:]))
# for each overlapped fusion junction
for fus in itl[(2 + len(iso)):]:
reads = fus.split()[1]
fus_start, fus_end = fusion_index[fus]
edge_annotations = [] # first or last exon flag
for iso_id in iso:
g, i, c, s = iso_id.split()[1:]
start = gene_info[iso_id][0][0]
end = gene_info[iso_id][-1][-1]
# fusion junction excesses boundaries of gene
# annotation
if fus_start < start - 10 or fus_end > end + 10:
continue
(fusion_info,
index,
edge) = map_fusion_to_iso(fus_start,
fus_end, s,
gene_info[iso_id])
if fusion_info:
fus_start_str = str(fus_start)
fus_end_str = str(fus_end)
bed_info = '\t'.join([chrom, fus_start_str,
fus_end_str,
'FUSIONJUNC/%s' % reads,
'0', s, fus_start_str,
fus_start_str, '0,0,0'])
bed = '\t'.join([bed_info, fusion_info, g, i,
index])
if not edge: # not first or last exon
outf.write(bed + '\n')
total.add(fus)
else: # first or last exon
edge_annotations.append(bed)
if edge_annotations: # first or last exon
for bed in edge_annotations:
outf.write(bed + '\n')
total.add(fus)
print('Annotated %d fusion junctions!' % len(total))
def annotate_fusion(ref_f, input_f, output_f):
"""
Align fusion juncrions to gene annotations
"""
print('Start to annotate fusion junctions...')
genes, gene_info = parse_ref1(ref_f) # gene annotations
fusions, fusion_index = parse_bed(input_f) # fusion junctions
total = set()
with open(output_f, 'w') as outf:
for chrom in genes:
# overlap gene annotations with fusion juncrions
result = Interval.overlapwith(genes[chrom].interval,
fusions[chrom])
for itl in result:
# extract gene annotations
iso = list(filter(lambda x: x.startswith('iso'), itl[2:]))
# for each overlapped fusion junction
for fus in itl[(2 + len(iso)):]:
reads = fus.split()[1]
fus_start, fus_end = fusion_index[fus]
edge_annotations = [] # first or last exon flag
for iso_id in iso:
g, i, c, s = iso_id.split()[1:]
start = gene_info[iso_id][0][0]
end = gene_info[iso_id][-1][-1]
# fusion junction excesses boundaries of gene
# annotation
if fus_start < start - 10 or fus_end > end + 10:
continue
(fusion_info, index,
edge) = map_fusion_to_iso(fus_start, fus_end, s,
gene_info[iso_id])
if fusion_info:
fus_start_str = str(fus_start)
fus_end_str = str(fus_end)
bed_info = '\t'.join([
chrom, fus_start_str, fus_end_str,
'FUSIONJUNC/%s' % reads, '0', s, fus_start_str,
fus_start_str, '0,0,0'
])
bed = '\t'.join(
[bed_info, fusion_info, g, i, index])
if not edge: # not first or last exon
outf.write(bed + '\n')
total.add(fus)
else: # first or last exon
edge_annotations.append(bed)
if edge_annotations: # first or last exon
for bed in edge_annotations:
outf.write(bed + '\n')
total.add(fus)
print('Annotated %d fusion junctions!' % len(total))
def annotate_fusion(ref_f, junc_bed, secondary_flag=0, denovo_flag=0):
"""
Align fusion juncrions to gene annotations
"""
print('Start to annotate fusion junctions...')
# gene annotations
genes, novel_genes, gene_info, chrom_info = parse_ref(ref_f, 1)
fusion_bed = junc_bed
fusions, fusion_index = parse_bed(fusion_bed) # fusion junctions
total = set()
annotated_fusion_f = 'annotated_fusion.txt.tmp'
with open(annotated_fusion_f, 'w') as outf:
for chrom in chrom_info:
# overlap gene annotations with fusion juncrions
result = []
# overlap genes
if chrom in genes:
result += Interval.overlapwith(genes[chrom].interval,
fusions[chrom])
# overlap novel genes in denovo mode
if denovo_flag and chrom in novel_genes:
result += Interval.overlapwith(novel_genes[chrom].interval,
fusions[chrom])
for itl in result:
# extract gene annotations
iso = list([x for x in itl[2:] if x.startswith('iso')])
# for each overlapped fusion junction
for fus in itl[(2 + len(iso)):]:
reads = fus.split()[1]
fus_start, fus_end = fusion_index[fus]
fus_loc = '%s\t%d\t%d\tFUSIONJUNC/%s' % (chrom, fus_start,
fus_end, reads)
edge_annotations = [] # first or last exon flag
secondary_exon = defaultdict(dict) # secondary exons
annotate_flag = 0
for iso_id in iso:
g, i, c, s = iso_id.split()[1:]
start = gene_info[iso_id][0][0]
end = gene_info[iso_id][-1][-1]
# fusion junction excesses boundaries of gene
# annotation
if fus_start < start - 10 or fus_end > end + 10:
if not secondary_flag:
continue
(fusion_info,
index,
edge,
secondary) = map_fusion_to_iso(fus_start,
fus_end, s,
gene_info[iso_id])
if fusion_info:
annotate_flag += 1
bed_info = '\t'.join([fus_loc, '0', s,
str(fus_start),
str(fus_start), '0,0,0'])
bed = '\t'.join([bed_info, fusion_info, g, i,
index])
if not edge: # not first or last exon
outf.write(bed + '\n')
total.add(fus)
else: # first or last exon
edge_annotations.append(bed)
elif secondary_flag and secondary is not None:
li, ri = secondary
gene = ':'.join([g, s])
if li is not None:
li = str(li)
secondary_exon['left'][gene] = ':'.join([i,
li])
if ri is not None:
ri = str(ri)
secondary_exon['right'][gene] = ':'.join([i,
ri])
if edge_annotations:
for bed in edge_annotations:
outf.write(bed + '\n')
total.add(fus)
if secondary_flag and not annotate_flag:
for gene in secondary_exon['left']:
if gene in secondary_exon['right']:
left = secondary_exon['left'][gene]
right = secondary_exon['right'][gene]
g, s = gene.split(':')
# for avoid dup, use fus_loc_new
fus_loc_new = fus_loc + '\t0\t%s' % s
outf.write('%s\t%s:%s\t%s:%s\n' % (fus_loc_new,
g, left, g,
right))
print('Annotated %d fusion junctions!' % len(total))
def extract_retained_intron(denovo_dir, tophat_dir, pAplus_dir, output_dir):
"""
Check each intron and fetch PIR
Modified from Braunschweig et al., Genome Research, 2014, gr-177790.
"""
print('Start to parse circular RNA introns...')
# set path
fusion_f = '%s/circularRNA_full.txt' % denovo_dir
pAminus_junc_f = tophat_dir + '/junctions.bed'
pAminus_junc = parse_junc(pAminus_junc_f)
pAminus_bam_f = tophat_dir + '/accepted_hits.bam'
pAminus_bam = pysam.AlignmentFile(pAminus_bam_f, 'rb')
pAplus_junc_f = '%s/junctions.bed' % pAplus_dir
pAplus_junc = parse_junc(pAplus_junc_f)
pAplus_bam_f = '%s/accepted_hits.bam' % pAplus_dir
pAplus_bam = pysam.AlignmentFile(pAplus_bam_f, 'rb')
excluded_region = defaultdict(list)
novel_region = defaultdict(list)
intron = defaultdict(list)
intron_list = set()
intron_info_list = {}
with open(fusion_f, 'r') as f:
for line in f:
chrom, start, end = line.split()[:3]
start = int(start)
end = int(end)
strand = line.split()[5]
circ_type = line.split()[13]
if circ_type == 'ciRNA': # not check ciRNAs
excluded_region[chrom].append([start, end])
continue
sizes = [int(x) for x in line.split()[10].split(',')]
offsets = [int(x) for x in line.split()[11].split(',')]
reads = line.split()[12]
gene, iso = line.split()[14:16]
for s, o in zip(sizes, offsets):
if gene.startswith('CUFF'):
novel_region[chrom].append([start + o, start + o + s])
else:
excluded_region[chrom].append([start + o, start + o + s])
if gene.startswith('CUFF'): # only check annotated introns
continue
num = int(line.split()[9])
for i in range(num - 1):
sta = start + offsets[i] + sizes[i]
end = start + offsets[i + 1]
if end - sta == 0:
continue
intron_info = '%s\t%d\t%d\t%s' % (chrom, sta, end, strand)
if intron_info in intron_list:
if int(reads) > int(intron_info_list[intron_info][2]):
intron_info_list[intron_info] = [gene, iso, reads]
continue
intron[chrom].append([sta, end, intron_info])
intron_list.add(intron_info)
intron_info_list[intron_info] = [gene, iso, reads]
intron_set = set()
for chrom in excluded_region:
intron_region = []
# retain introns covered by novel assembled transcripts
# combined_region = Interval(novel_region[chrom]).interval
# for region in Interval.overlapwith(combined_region, intron[chrom]):
# retain all intron regions in this step
for region in intron[chrom]:
if len(region) >= 3:
for intron_info in region[2:]:
chrom, start, end = intron_info.split()[:3]
intron_region.append([int(start), int(end), intron_info])
intron_set.add(intron_info)
# remove introns overlapped with annotated exons
combined_region = Interval(excluded_region[chrom]).interval
for region in Interval.overlapwith(combined_region, intron_region):
if len(region) >= 3:
for intron_info in region[2:]:
intron_set.discard(intron_info)
output_f = '%s/all_intron_info.txt' % output_dir
# import pdb;pdb.set_trace()
with open(output_f, 'w') as output:
total_i_n = len(intron_set)
finished_n = 0
for intron in intron_set:
chrom, sta, end, strand = intron.split()
intron_info = '\t'.join([chrom, sta, end])
sta = int(sta)
end = int(end)
# fetch junctions for circular RNAs
circ_junc_read = pAminus_junc[intron_info]
circ_left_read = fetch_read(pAminus_bam, chrom, sta - 8, sta + 8)
circ_right_read = fetch_read(pAminus_bam, chrom, end - 8, end + 8)
circ_ri_read = circ_left_read + circ_right_read
circ_intron_read = fetch_read(pAminus_bam, chrom, sta, end, flag=0)
# calculate PIR for circular RNAs
if circ_ri_read == 0 and circ_junc_read == 0:
pir_circ = 0
else:
pir_circ = 100.0 * circ_ri_read / (circ_ri_read +
2 * circ_junc_read)
# exact binomial test for circular RNAs
m = min(circ_left_read, circ_right_read, circ_intron_read)
n = m + max(circ_left_read, circ_right_read, circ_intron_read)
p = 1 / 3.5
p1 = binom.cdf(m, n, p) # one-side binomial test
# fetch junctions for linear RNAs
linear_junc_read = pAplus_junc[intron_info]
linear_left_read = fetch_read(pAplus_bam, chrom, sta - 8, sta + 8)
linear_right_read = fetch_read(pAplus_bam, chrom, end - 8, end + 8)
linear_ri_read = linear_left_read + linear_right_read
linear_intron_read = fetch_read(pAplus_bam, chrom, sta, end,
flag=0)
# calculate PIR for linear RNAs
if linear_ri_read == 0 and linear_junc_read == 0:
pir_linear = 0
else:
pir_linear = 100.0 * linear_ri_read / (linear_ri_read +
linear_junc_read * 2)
# exact binomial test for linear RNAs
m = min(linear_left_read, linear_right_read,
linear_intron_read)
n = m + max(linear_left_read, linear_right_read,
linear_intron_read)
p = 1 / 3.5
p2 = binom.cdf(m, n, p) # one-side binomial test
info = '\t'.join(str(round(float(x), 3))
for x in (pir_circ, pir_linear, p1, p2,
circ_ri_read,
circ_junc_read,
circ_intron_read,
linear_ri_read,
linear_junc_read,
linear_intron_read))
other_info = '\t'.join(intron_info_list[intron])
output.write('\t'.join([chrom, str(sta), str(end), 'Intron', '0',
strand, other_info, info]))
output.write('\n')
finished_n += 1
sys.stdout.write("Progress: %d/%d \r" % (finished_n, total_i_n) )
sys.stdout.flush()
print('Complete parsing circular RNA introns!')
def extract_retained_intron(denovo_dir, tophat_dir, pAplus_dir):
"""
Check each intron and fetch PIR
Modified from Braunschweig et al., Genome Research, 2014, gr-177790.
"""
print('Start to parse circular RNA introns...')
# set path
fusion_f = '%s/circ_fusion.txt' % denovo_dir
pAminus_junc_f = tophat_dir + '/junctions.bed'
pAminus_junc = parse_junc(pAminus_junc_f)
pAminus_bam_f = tophat_dir + '/accepted_hits.bam'
pAminus_bam = pysam.AlignmentFile(pAminus_bam_f, 'rb')
pAplus_junc_f = '%s/junctions.bed' % pAplus_dir
pAplus_junc = parse_junc(pAplus_junc_f)
pAplus_bam_f = '%s/accepted_hits.bam' % pAplus_dir
pAplus_bam = pysam.AlignmentFile(pAplus_bam_f, 'rb')
excluded_region = defaultdict(list)
novel_region = defaultdict(list)
intron = defaultdict(list)
intron_list = set()
intron_info_list = {}
with open(fusion_f, 'r') as f:
for line in f:
chrom, start, end = line.split()[:3]
start = int(start)
end = int(end)
strand = line.split()[5]
circ_type = line.split()[13]
if circ_type == 'ciRNA': # not check ciRNAs
excluded_region[chrom].append([start, end])
continue
sizes = [int(x) for x in line.split()[10].split(',')]
offsets = [int(x) for x in line.split()[11].split(',')]
reads = line.split()[12]
gene, iso = line.split()[14:16]
for s, o in zip(sizes, offsets):
if gene.startswith('CUFF'):
novel_region[chrom].append([start + o, start + o + s])
else:
excluded_region[chrom].append([start + o, start + o + s])
if gene.startswith('CUFF'): # only check annotated introns
continue
num = int(line.split()[9])
for i in range(num - 1):
sta = start + offsets[i] + sizes[i]
end = start + offsets[i + 1]
if end - sta == 0:
continue
intron_info = '%s\t%d\t%d\t%s' % (chrom, sta, end, strand)
if intron_info in intron_list:
if int(reads) > int(intron_info_list[intron_info][2]):
intron_info_list[intron_info] = [gene, iso, reads]
continue
intron[chrom].append([sta, end, intron_info])
intron_list.add(intron_info)
intron_info_list[intron_info] = [gene, iso, reads]
intron_set = set()
for chrom in excluded_region:
intron_region = []
# retain introns covered by novel assembled transcripts
combined_region = Interval(novel_region[chrom]).interval
for region in Interval.overlapwith(combined_region, intron[chrom]):
if len(region) >= 3:
for intron_info in region[2:]:
chrom, start, end = intron_info.split()[:3]
intron_region.append([int(start), int(end), intron_info])
intron_set.add(intron_info)
# remove introns overlapped with annotated exons
combined_region = Interval(excluded_region[chrom]).interval
for region in Interval.overlapwith(combined_region, intron_region):
if len(region) >= 3:
for intron_info in region[2:]:
intron_set.discard(intron_info)
output_f = '%s/all_intron_info.txt' % denovo_dir
with open(output_f, 'w') as output:
for intron in intron_set:
chrom, sta, end, strand = intron.split()
intron_info = '\t'.join([chrom, sta, end])
sta = int(sta)
end = int(end)
# fetch junctions for circular RNAs
circ_junc_read = pAminus_junc[intron_info]
circ_left_read = fetch_read(pAminus_bam, chrom, sta - 8, sta + 8)
circ_right_read = fetch_read(pAminus_bam, chrom, end - 8, end + 8)
circ_ri_read = circ_left_read + circ_right_read
circ_intron_read = fetch_read(pAminus_bam, chrom, sta, end, flag=0)
# calculate PIR for circular RNAs
if circ_ri_read == 0 and circ_junc_read == 0:
pir_circ = 0
else:
pir_circ = 100.0 * circ_ri_read / (circ_ri_read +
2 * circ_junc_read)
# exact binomial test for circular RNAs
m = min(circ_left_read, circ_right_read, circ_intron_read)
n = m + max(circ_left_read, circ_right_read, circ_intron_read)
p = 1 / 3.5
p1 = binom.cdf(m, n, p) # one-side binomial test
# fetch junctions for linear RNAs
linear_junc_read = pAplus_junc[intron_info]
linear_left_read = fetch_read(pAplus_bam, chrom, sta - 8, sta + 8)
linear_right_read = fetch_read(pAplus_bam, chrom, end - 8, end + 8)
linear_ri_read = linear_left_read + linear_right_read
linear_intron_read = fetch_read(pAplus_bam, chrom, sta, end,
flag=0)
# calculate PIR for linear RNAs
if linear_ri_read == 0 and linear_junc_read == 0:
pir_linear = 0
else:
pir_linear = 100.0 * linear_ri_read / (linear_ri_read +
linear_junc_read * 2)
# exact binomial test for linear RNAs
m = min(linear_left_read, linear_right_read,
linear_intron_read)
n = m + max(linear_left_read, linear_right_read,
linear_intron_read)
p = 1 / 3.5
p2 = binom.cdf(m, n, p) # one-side binomial test
info = '\t'.join(str(round(x, 3))
for x in (pir_circ, pir_linear, p1, p2,
circ_ri_read,
circ_junc_read,
circ_intron_read,
linear_ri_read,
linear_junc_read,
linear_intron_read))
other_info = '\t'.join(intron_info_list[intron])
output.write('\t'.join([chrom, str(sta), str(end), 'Intron', '0',
strand, other_info, info]))
output.write('\n')
print('Complete parsing circular RNA introns!')