def pair_clusters_by_bin((key, fwd_clusters, rev_clusters, bam_file_name, verbose)):
print "processing cluster pairs on %s" % (key)
#print "pairing clusters in parallel for chr %s" % fwd_clusters[0].chr
non_overlapping_fwd_clusters = remove_overlapping_clusters(fwd_clusters)
if verbose:
print "non overlapping fwd clusters\t%d" % (len(non_overlapping_fwd_clusters))
non_overlapping_rev_clusters = remove_overlapping_clusters(rev_clusters)
if verbose:
print "non overlapping rev clusters\t%d" % (len(non_overlapping_rev_clusters))
proper_pair_bam = pysam.Samfile(bam_file_name, "rb")
#print "haha"
#print "ok1"
#pair clusters by genomic location, keeping track of which indices in the array have been paired, so that you can pick out the unpaired ones after
cluster_pairs = []
paired_fwd_clusters_indices = []
paired_rev_clusters_indices = []
for fwd_index, fwd_cluster in enumerate(non_overlapping_fwd_clusters):
for rev_index, rev_cluster in enumerate(non_overlapping_rev_clusters):
if fwd_cluster.is_overlapping_strict(rev_cluster):
new_cluster_pair = ClusterPair(fwd_cluster, rev_cluster)
#print new_cluster_pair.get_chr()
reads = proper_pair_bam.fetch(new_cluster_pair.get_chr(), new_cluster_pair.get_insertion_int_start(), new_cluster_pair.get_insertion_int_end())
new_cluster_pair.calc_zygosity(reads)
#print "poop"
if new_cluster_pair.get_insertion_int_end() < new_cluster_pair.get_insertion_int_start():
if True:
print "cluster pair not paired!"
else:
cluster_pairs.append(new_cluster_pair)
paired_fwd_clusters_indices.append(fwd_index)
paired_rev_clusters_indices.append(rev_index)
#make lists of unpaired clusters
unpaired_fwd_clusters = []
unpaired_rev_clusters = []
for fwd_index in range(len(non_overlapping_fwd_clusters)):
if fwd_index not in paired_fwd_clusters_indices:
unpaired_fwd_clusters.append(non_overlapping_fwd_clusters[fwd_index])
for rev_index in range(len(non_overlapping_rev_clusters)):
if rev_index not in paired_rev_clusters_indices:
unpaired_rev_clusters.append(non_overlapping_rev_clusters[rev_index])
return (cluster_pairs, unpaired_fwd_clusters, unpaired_rev_clusters)
def pair_clusters_by_bin((key, fwd_clusters, rev_clusters, bam_file_name, verbose, bed_file_handle, streaming, min_cluster_size)):
print "processing cluster pairs on %s" % (key)
#print "pairing clusters in parallel for chr %s" % fwd_clusters[0].chr
non_overlapping_fwd_clusters = remove_overlapping_clusters(fwd_clusters,min_cluster_size)
if verbose:
print "non overlapping fwd clusters\t%d" % (len(non_overlapping_fwd_clusters))
non_overlapping_rev_clusters = remove_overlapping_clusters(rev_clusters,min_cluster_size)
if verbose:
print "non overlapping rev clusters\t%d" % (len(non_overlapping_rev_clusters))
if not streaming:
proper_pair_bam = pysam.Samfile(bam_file_name, "rb")
#print "haha"
#print "ok1"
#pair clusters by genomic location, keeping track of which indices in the array have been paired, so that you can pick out the unpaired ones after
cluster_pairs = []
paired_fwd_clusters_indices = []
paired_rev_clusters_indices = []
last_intersect=0
bed_string = ""
for fwd_index in range(0,len(non_overlapping_fwd_clusters)):
#if fwd_cluster.num_reads < min_cluster_size:
# continue
fwd_cluster=non_overlapping_fwd_clusters[fwd_index]
for rev_index in range(last_intersect, len(non_overlapping_rev_clusters)):
#if rev_cluster.num_reads < min_cluster_size:
# continue
rev_cluster=non_overlapping_rev_clusters[rev_index]
if fwd_cluster.is_overlapping_strict(rev_cluster):
new_cluster_pair = ClusterPair(fwd_cluster, rev_cluster)
last_intersect=rev_index
#print new_cluster_pair.get_chr()
if not streaming:
reads = proper_pair_bam.fetch(new_cluster_pair.get_chr(), new_cluster_pair.get_insertion_int_start(), new_cluster_pair.get_insertion_int_end())
new_cluster_pair.calc_zygosity(reads)
else:
bed_line = new_cluster_pair.to_bed()
bed_string = bed_string + "\n" + bed_line
#print "poop"
if new_cluster_pair.get_insertion_int_end() < new_cluster_pair.get_insertion_int_start():
if True:
print "cluster pair not paired!"
else:
cluster_pairs.append(new_cluster_pair)
paired_fwd_clusters_indices.append(fwd_index)
paired_rev_clusters_indices.append(rev_index)
elif fwd_cluster.intersection_end < rev_cluster.intersection_start:
break
#make lists of unpaired clusters
unpaired_fwd_clusters = []
unpaired_rev_clusters = []
for fwd_index in range(len(non_overlapping_fwd_clusters)):
if fwd_index not in paired_fwd_clusters_indices:
unpaired_fwd_clusters.append(non_overlapping_fwd_clusters[fwd_index])
for rev_index in range(len(non_overlapping_rev_clusters)):
if rev_index not in paired_rev_clusters_indices:
unpaired_rev_clusters.append(non_overlapping_rev_clusters[rev_index])
if streaming:
return (cluster_pairs, unpaired_fwd_clusters, unpaired_rev_clusters, bed_string)
else:
return (cluster_pairs, unpaired_fwd_clusters, unpaired_rev_clusters)
def generate_clusters(self, verbose, psorted_bamfile_name, bed_file_handle, streaming, min_cluster_size):
##################### BEGIN NON PARALLEL VERSION ######################################
#cluster fwd intervals
fwd_read_pairs = [read_pair for read_pair in self.read_pair_list if read_pair.interval_direction == "fwd"]
fwd_clusters = cluster_read_pairs_all(fwd_read_pairs)
print "******************total fwd clusters found: %d" % len(fwd_clusters)
non_overlapping_fwd_clusters = remove_overlapping_clusters(fwd_clusters,min_cluster_size)
print "******************total fwd non-overlapping clusters found: %d" % len(non_overlapping_fwd_clusters)
#cluster rev intervals
rev_read_pairs = [read_pair for read_pair in self.read_pair_list if read_pair.interval_direction == "rev"]
rev_clusters = cluster_read_pairs_all(rev_read_pairs)
print "******************total rev clusters found: %d" % len(rev_clusters)
non_overlapping_rev_clusters = remove_overlapping_clusters(rev_clusters,min_cluster_size)
print "******************total rev non-overlapping clusters found: %d" % len(non_overlapping_rev_clusters)
#bam_file_name = output_prefix + ".proper_pair.sorted.bam"
psorted_bamfile = pysam.Samfile(psorted_bamfile_name, "rb")
#pair clusters by genomic location, keeping track of which indices in the array have been paired, so that you can pick out the unpaired ones after
cluster_pairs = []
paired_fwd_clusters_indices = []
paired_rev_clusters_indices = []
bed_string = ""
last_intersect=0
# iterate over combinations of fwd and rev clusters, skipping if clusters dont meet min size requirements
for fwd_index in range(0,len(non_overlapping_fwd_clusters)):
#if fwd_cluster.num_reads < min_cluster_size:
# continue
fwd_cluster=non_overlapping_fwd_clusters[fwd_index]
for rev_index in range(last_intersect, len(non_overlapping_rev_clusters)):
#if rev_cluster.num_reads < min_cluster_size:
# continue
rev_cluster=non_overlapping_rev_clusters[rev_index]
if fwd_cluster.is_overlapping_strict(rev_cluster):
last_intersect=rev_index
new_cluster_pair = ClusterPair(fwd_cluster, rev_cluster)
if not streaming:
reads = proper_pair_bam.fetch(new_cluster_pair.get_chr(), new_cluster_pair.get_insertion_int_start(), new_cluster_pair.get_insertion_int_end())
new_cluster_pair.calc_zygosity(reads)
else:
bed_line = new_cluster_pair.to_bed()
if bed_string == "":
bed_string = bed_line
else:
bed_string = bed_string + "\n" + bed_line
if new_cluster_pair.insertion_int_end < new_cluster_pair.insertion_int_start:
if True:
print "cluster pair not paired!"
else:
cluster_pairs.append(new_cluster_pair)
paired_fwd_clusters_indices.append(fwd_index)
paired_rev_clusters_indices.append(rev_index)
elif fwd_cluster.intersection_end < rev_cluster.intersection_start:
break
#make lists of unpaired clusters
unpaired_fwd_clusters = []
unpaired_rev_clusters = []
for fwd_index in range(len(non_overlapping_fwd_clusters)):
if fwd_index not in paired_fwd_clusters_indices:
unpaired_fwd_clusters.append(non_overlapping_fwd_clusters[fwd_index])
for rev_index in range(len(non_overlapping_rev_clusters)):
if rev_index not in paired_rev_clusters_indices:
unpaired_rev_clusters.append(non_overlapping_rev_clusters[rev_index])
print "******************total cluster pairs found: %d" % len(cluster_pairs)
if verbose:
for (fwd_cluster, rev_cluster) in cluster_pairs:
print "*************************cluster_pair:**************************************"
print "fwd cluster:"
print "cluster coordinates: %s %d %d" % (fwd_cluster[0].interval_chr, fwd_cluster[0].interval_start, fwd_cluster[-1].interval_end )
print " ".join(read.str_int() for read in fwd_cluster)
print " ".join(read.str_TE_annot_list() for read in fwd_cluster)
print "rev cluster:"
print "cluster coordinates: %s %d %d" % (rev_cluster[0].interval_chr, rev_cluster[0].interval_start, rev_cluster[-1].interval_end )
print " ".join(read.str_int() for read in rev_cluster)
print " ".join(read.str_TE_annot_list() for read in rev_cluster)
return (cluster_pairs, unpaired_fwd_clusters, unpaired_rev_clusters, bed_string)
def pair_clusters_by_bin(
(key, fwd_clusters, rev_clusters, bam_file_name, verbose, bed_file_handle,
streaming, min_cluster_size)):
print "processing cluster pairs on %s" % (key)
#print "pairing clusters in parallel for chr %s" % fwd_clusters[0].chr
non_overlapping_fwd_clusters = remove_overlapping_clusters(
fwd_clusters, min_cluster_size)
if verbose:
print "non overlapping fwd clusters\t%d" % (
len(non_overlapping_fwd_clusters))
non_overlapping_rev_clusters = remove_overlapping_clusters(
rev_clusters, min_cluster_size)
if verbose:
print "non overlapping rev clusters\t%d" % (
len(non_overlapping_rev_clusters))
if not streaming:
proper_pair_bam = pysam.Samfile(bam_file_name, "rb")
#print "haha"
#print "ok1"
#pair clusters by genomic location, keeping track of which indices in the array have been paired, so that you can pick out the unpaired ones after
cluster_pairs = []
paired_fwd_clusters_indices = []
paired_rev_clusters_indices = []
last_intersect = 0
bed_string = ""
for fwd_index in range(0, len(non_overlapping_fwd_clusters)):
#if fwd_cluster.num_reads < min_cluster_size:
# continue
fwd_cluster = non_overlapping_fwd_clusters[fwd_index]
for rev_index in range(last_intersect,
len(non_overlapping_rev_clusters)):
#if rev_cluster.num_reads < min_cluster_size:
# continue
rev_cluster = non_overlapping_rev_clusters[rev_index]
if fwd_cluster.is_overlapping_strict(rev_cluster):
new_cluster_pair = ClusterPair(fwd_cluster, rev_cluster)
last_intersect = rev_index
#print new_cluster_pair.get_chr()
if not streaming:
reads = proper_pair_bam.fetch(
new_cluster_pair.get_chr(),
new_cluster_pair.get_insertion_int_start(),
new_cluster_pair.get_insertion_int_end())
new_cluster_pair.calc_zygosity(reads)
else:
bed_line = new_cluster_pair.to_bed()
bed_string = bed_string + "\n" + bed_line
#print "poop"
if new_cluster_pair.get_insertion_int_end(
) < new_cluster_pair.get_insertion_int_start():
if True:
print "cluster pair not paired!"
else:
cluster_pairs.append(new_cluster_pair)
paired_fwd_clusters_indices.append(fwd_index)
paired_rev_clusters_indices.append(rev_index)
elif fwd_cluster.intersection_end < rev_cluster.intersection_start:
break
#make lists of unpaired clusters
unpaired_fwd_clusters = []
unpaired_rev_clusters = []
for fwd_index in range(len(non_overlapping_fwd_clusters)):
if fwd_index not in paired_fwd_clusters_indices:
unpaired_fwd_clusters.append(
non_overlapping_fwd_clusters[fwd_index])
for rev_index in range(len(non_overlapping_rev_clusters)):
if rev_index not in paired_rev_clusters_indices:
unpaired_rev_clusters.append(
non_overlapping_rev_clusters[rev_index])
if streaming:
return (cluster_pairs, unpaired_fwd_clusters, unpaired_rev_clusters,
bed_string)
else:
return (cluster_pairs, unpaired_fwd_clusters, unpaired_rev_clusters)
def generate_clusters(self, verbose, psorted_bamfile_name, bed_file_handle,
streaming, min_cluster_size):
##################### BEGIN NON PARALLEL VERSION ######################################
#cluster fwd intervals
fwd_read_pairs = [
read_pair for read_pair in self.read_pair_list
if read_pair.interval_direction == "fwd"
]
fwd_clusters = cluster_read_pairs_all(fwd_read_pairs)
print "******************total fwd clusters found: %d" % len(
fwd_clusters)
non_overlapping_fwd_clusters = remove_overlapping_clusters(
fwd_clusters, min_cluster_size)
print "******************total fwd non-overlapping clusters found: %d" % len(
non_overlapping_fwd_clusters)
#cluster rev intervals
rev_read_pairs = [
read_pair for read_pair in self.read_pair_list
if read_pair.interval_direction == "rev"
]
rev_clusters = cluster_read_pairs_all(rev_read_pairs)
print "******************total rev clusters found: %d" % len(
rev_clusters)
non_overlapping_rev_clusters = remove_overlapping_clusters(
rev_clusters, min_cluster_size)
print "******************total rev non-overlapping clusters found: %d" % len(
non_overlapping_rev_clusters)
#bam_file_name = output_prefix + ".proper_pair.sorted.bam"
psorted_bamfile = pysam.Samfile(psorted_bamfile_name, "rb")
#pair clusters by genomic location, keeping track of which indices in the array have been paired, so that you can pick out the unpaired ones after
cluster_pairs = []
paired_fwd_clusters_indices = []
paired_rev_clusters_indices = []
bed_string = ""
last_intersect = 0
# iterate over combinations of fwd and rev clusters, skipping if clusters dont meet min size requirements
for fwd_index in range(0, len(non_overlapping_fwd_clusters)):
#if fwd_cluster.num_reads < min_cluster_size:
# continue
fwd_cluster = non_overlapping_fwd_clusters[fwd_index]
for rev_index in range(last_intersect,
len(non_overlapping_rev_clusters)):
#if rev_cluster.num_reads < min_cluster_size:
# continue
rev_cluster = non_overlapping_rev_clusters[rev_index]
if fwd_cluster.is_overlapping_strict(rev_cluster):
last_intersect = rev_index
new_cluster_pair = ClusterPair(fwd_cluster, rev_cluster)
if not streaming:
reads = proper_pair_bam.fetch(
new_cluster_pair.get_chr(),
new_cluster_pair.get_insertion_int_start(),
new_cluster_pair.get_insertion_int_end())
new_cluster_pair.calc_zygosity(reads)
else:
bed_line = new_cluster_pair.to_bed()
if bed_string == "":
bed_string = bed_line
else:
bed_string = bed_string + "\n" + bed_line
if new_cluster_pair.insertion_int_end < new_cluster_pair.insertion_int_start:
if True:
print "cluster pair not paired!"
else:
cluster_pairs.append(new_cluster_pair)
paired_fwd_clusters_indices.append(fwd_index)
paired_rev_clusters_indices.append(rev_index)
elif fwd_cluster.intersection_end < rev_cluster.intersection_start:
break
#make lists of unpaired clusters
unpaired_fwd_clusters = []
unpaired_rev_clusters = []
for fwd_index in range(len(non_overlapping_fwd_clusters)):
if fwd_index not in paired_fwd_clusters_indices:
unpaired_fwd_clusters.append(
non_overlapping_fwd_clusters[fwd_index])
for rev_index in range(len(non_overlapping_rev_clusters)):
if rev_index not in paired_rev_clusters_indices:
unpaired_rev_clusters.append(
non_overlapping_rev_clusters[rev_index])
print "******************total cluster pairs found: %d" % len(
cluster_pairs)
if verbose:
for (fwd_cluster, rev_cluster) in cluster_pairs:
print "*************************cluster_pair:**************************************"
print "fwd cluster:"
print "cluster coordinates: %s %d %d" % (
fwd_cluster[0].interval_chr, fwd_cluster[0].interval_start,
fwd_cluster[-1].interval_end)
print " ".join(read.str_int() for read in fwd_cluster)
print " ".join(read.str_TE_annot_list()
for read in fwd_cluster)
print "rev cluster:"
print "cluster coordinates: %s %d %d" % (
rev_cluster[0].interval_chr, rev_cluster[0].interval_start,
rev_cluster[-1].interval_end)
print " ".join(read.str_int() for read in rev_cluster)
print " ".join(read.str_TE_annot_list()
for read in rev_cluster)
return (cluster_pairs, unpaired_fwd_clusters, unpaired_rev_clusters,
bed_string)
def generate_clusters(self, verbose, psorted_bamfile_name):
##################### BEGIN NON PARALLEL VERSION ######################################
#cluster fwd intervals
fwd_read_pairs = [read_pair for read_pair in self.read_pair_list if read_pair.interval_direction == "fwd"]
fwd_clusters = cluster_read_pairs_all(fwd_read_pairs)
print "******************total fwd clusters found: %d" % len(fwd_clusters)
non_overlapping_fwd_clusters = remove_overlapping_clusters(fwd_clusters)
print "******************total fwd non-overlapping clusters found: %d" % len(non_overlapping_fwd_clusters)
#cluster rev intervals
rev_read_pairs = [read_pair for read_pair in self.read_pair_list if read_pair.interval_direction == "rev"]
rev_clusters = cluster_read_pairs_all(rev_read_pairs)
print "******************total rev clusters found: %d" % len(rev_clusters)
non_overlapping_rev_clusters = remove_overlapping_clusters(rev_clusters)
print "******************total rev non-overlapping clusters found: %d" % len(non_overlapping_rev_clusters)
#bam_file_name = output_prefix + ".proper_pair.sorted.bam"
psorted_bamfile = pysam.Samfile(psorted_bamfile_name, "rb")
#pair clusters by genomic location, keeping track of which indices in the array have been paired, so that you can pick out the unpaired ones after
cluster_pairs = []
paired_fwd_clusters_indices = []
paired_rev_clusters_indices = []
for fwd_index, fwd_cluster in enumerate(non_overlapping_fwd_clusters):
for rev_index, rev_cluster in enumerate(non_overlapping_rev_clusters):
if fwd_cluster.is_overlapping_strict(rev_cluster):
new_cluster_pair = ClusterPair(fwd_cluster, rev_cluster)
reads = psorted_bamfile.fetch(new_cluster_pair.get_chr(), new_cluster_pair.get_insertion_int_start(), new_cluster_pair.get_insertion_int_end())
new_cluster_pair.calc_zygosity(reads)
if new_cluster_pair.insertion_int_end < new_cluster_pair.insertion_int_start:
if True:
print "cluster pair not paired!"
else:
cluster_pairs.append(new_cluster_pair)
paired_fwd_clusters_indices.append(fwd_index)
paired_rev_clusters_indices.append(rev_index)
#make lists of unpaired clusters
unpaired_fwd_clusters = []
unpaired_rev_clusters = []
for fwd_index in range(len(non_overlapping_fwd_clusters)):
if fwd_index not in paired_fwd_clusters_indices:
unpaired_fwd_clusters.append(non_overlapping_fwd_clusters[fwd_index])
for rev_index in range(len(non_overlapping_rev_clusters)):
if rev_index not in paired_rev_clusters_indices:
unpaired_rev_clusters.append(non_overlapping_rev_clusters[rev_index])
print "******************total cluster pairs found: %d" % len(cluster_pairs)
if verbose:
for (fwd_cluster, rev_cluster) in cluster_pairs:
print "*************************cluster_pair:**************************************"
print "fwd cluster:"
print "cluster coordinates: %s %d %d" % (fwd_cluster[0].interval_chr, fwd_cluster[0].interval_start, fwd_cluster[-1].interval_end )
print " ".join(read.str_int() for read in fwd_cluster)
print " ".join(read.str_TE_annot_list() for read in fwd_cluster)
print "rev cluster:"
print "cluster coordinates: %s %d %d" % (rev_cluster[0].interval_chr, rev_cluster[0].interval_start, rev_cluster[-1].interval_end )
print " ".join(read.str_int() for read in rev_cluster)
print " ".join(read.str_TE_annot_list() for read in rev_cluster)
return (cluster_pairs, unpaired_fwd_clusters, unpaired_rev_clusters)
