def get_highest_coverage_isoforms(input_file, gene_file):
# place overlapping chimeras into clusters
logging.debug("Building isoform cluster lookup table")
transcript_cluster_map = build_transcript_cluster_map(open(gene_file))
# build a lookup table to get genome coordinates from transcript
# coordinates
transcript_genome_map = build_transcript_genome_map(open(gene_file))
cluster_chimera_dict = collections.defaultdict(lambda: [])
for c in Chimera.parse(open(input_file)):
# TODO: adjust this to score chimeras differently!
key = (c.name, c.get_num_frags())
# get cluster of overlapping genes
cluster5p = transcript_cluster_map[c.tx_name_5p]
cluster3p = transcript_cluster_map[c.tx_name_3p]
# get genomic positions of breakpoints
coord5p = transcript_to_genome_pos(c.tx_name_5p, c.tx_end_5p-1, transcript_genome_map)
coord3p = transcript_to_genome_pos(c.tx_name_3p, c.tx_start_3p, transcript_genome_map)
# add to dictionary
cluster_chimera_dict[(cluster5p,cluster3p,coord5p,coord3p)].append(key)
# choose highest coverage chimeras within each pair of clusters
logging.debug("Finding highest coverage isoforms")
kept_chimeras = set()
for stats_list in cluster_chimera_dict.itervalues():
stats_dict = collections.defaultdict(lambda: set())
for stats_info in stats_list:
# index chimera names
stats_dict[stats_info[1:]].add(stats_info[0])
# find highest scoring key
sorted_keys = sorted(stats_dict.keys(), reverse=True)
kept_chimeras.update(stats_dict[sorted_keys[0]])
return kept_chimeras
def get_chimera_groups(input_file, gene_file):
# build a lookup table to get gene clusters from transcript name
transcript_cluster_map = build_transcript_cluster_map(open(gene_file))
# build a lookup table to get genome coordinates from transcript
# coordinates
# TODO: can either group by exact breakpoint, or just by
# gene cluster
# transcript_genome_map = build_transcript_genome_map(open(gene_file))
# group chimeras in the same genomic cluster with the same
# breakpoint
cluster_chimera_dict = collections.defaultdict(lambda: [])
for c in Chimera.parse(open(input_file)):
# get cluster of overlapping genes
cluster5p = transcript_cluster_map[c.tx_name_5p]
cluster3p = transcript_cluster_map[c.tx_name_3p]
# get genomic positions of breakpoints
#coord5p = transcript_to_genome_pos(c.partner5p.tx_name, c.partner5p.end-1, transcript_genome_map)
#coord3p = transcript_to_genome_pos(c.partner3p.tx_name, c.partner3p.start, transcript_genome_map)
# add to dictionary
cluster_chimera_dict[(cluster5p,cluster3p)].append(c)
# TODO: use this grouping instead?
#cluster_chimera_dict[(cluster5p,cluster3p,coord5p,coord3p)].append(c)
for key,chimeras in cluster_chimera_dict.iteritems():
yield key,chimeras
