def output_filtered_comparisons(self, output_dir=None,
sort_column="bayes_factor",
columns_to_write=[#"event_name",
"gene_id",
"gene_symbol",
"sample1_posterior_mean",
"sample1_ci_low",
"sample1_ci_high",
"sample2_posterior_mean",
"sample2_ci_low",
"sample2_ci_high",
"diff",
"bayes_factor",
"isoforms",
"sample1_counts",
"sample1_assigned_counts",
"sample2_counts",
"sample2_assigned_counts",
"chrom",
"strand",
"mRNA_starts",
"mRNA_ends"]):
"""
Output filtered comparisons table.
"""
if output_dir == None:
output_dir = self.misowrap_obj.comparisons_dir
# Output each file by event type
output_dir = os.path.join(output_dir, "filtered_events")
print "Outputting filtered events..."
print " - Output dir: %s" %(output_dir)
utils.make_dir(output_dir)
for event_type, filtered_df in self.filtered_events.iteritems():
curr_output_dir = os.path.join(output_dir, event_type)
print "Event type: %s" %(event_type)
# View by comparison
comparison_labels = \
utils.unique_list(filtered_df.index.get_level_values(0))
print "Outputting %d comparisons" %(len(comparison_labels))
for label in comparison_labels:
print "Comparison: %s" %(label)
comparison_output_dir = os.path.join(curr_output_dir,
label)
utils.make_dir(comparison_output_dir)
output_filename = os.path.join(comparison_output_dir,
"%s.%s.filtered.miso_bf" \
%(label,
event_type))
print "Outputting to: %s" %(output_filename)
curr_df = filtered_df.ix[label].sort_index(by=sort_column,
ascending=False)
curr_df.to_csv(output_filename,
sep=self.delimiter,
float_format="%.4f",
cols=columns_to_write)
def new_recs():
for gene_recs in list(events_db.iter_by_parent_childs()):
gene_rec = gene_recs[0]
event_id = gene_rec.id
# Use existing IDs if present
if "ensgene_id" in gene_rec.attributes:
ensgene_id = gene_rec.attributes["ensg_id"][0]
else:
ensgene_id = "NA"
if "refseq_id" in gene_rec.attributes:
refseq_id = gene_rec.attributes["refseq_id"][0]
else:
refseq_id = "NA"
if "gene_symbol" in gene_rec.attributes:
gene_symbol = gene_rec.attributes["gsymbol"][0]
else:
gene_symbol = "NA"
if event_id in event_genes_to_info:
event_info = event_genes_to_info[event_id]
ensgene_ids = \
utils.unique_list(event_info["ensg_id"])
if len(ensgene_ids) > 0 and ensgene_ids[0] != "NA":
ensgene_id = ",".join(ensgene_ids)
refseq_ids = \
utils.unique_list(event_info["refseq_id"])
if len(refseq_ids) > 0 and refseq_ids[0] != "NA":
refseq_id = ",".join(refseq_ids)
gene_symbols = \
utils.unique_list(event_info["gsymbol"])
if len(gene_symbols) > 0 and gene_symbols[0] != "NA":
gene_symbol = ",".join(gene_symbols)
gene_rec.attributes["ensg_id"] = [ensgene_id]
gene_rec.attributes["refseq_id"] = [refseq_id]
gene_rec.attributes["gsymbol"] = [gene_symbol]
# Yield all the gene's records
for g in gene_recs:
yield g
def new_recs():
for gene_recs in list(events_db.iter_by_parent_childs()):
gene_rec = gene_recs[0]
event_id = gene_rec.id
# Use existing IDs if present
if "ensgene_id" in gene_rec.attributes:
ensgene_id = gene_rec.attributes["ensg_id"][0]
else:
ensgene_id = "NA"
if "refseq_id" in gene_rec.attributes:
refseq_id = gene_rec.attributes["refseq_id"][0]
else:
refseq_id = "NA"
if "gene_symbol" in gene_rec.attributes:
gene_symbol = gene_rec.attributes["gsymbol"][0]
else:
gene_symbol = "NA"
if event_id in event_genes_to_info:
event_info = event_genes_to_info[event_id]
ensgene_ids = \
utils.unique_list(event_info["ensg_id"])
if len(ensgene_ids) > 0 and ensgene_ids[0] != "NA":
ensgene_id = ",".join(ensgene_ids)
refseq_ids = \
utils.unique_list(event_info["refseq_id"])
if len(refseq_ids) > 0 and refseq_ids[0] != "NA":
refseq_id = ",".join(refseq_ids)
gene_symbols = \
utils.unique_list(event_info["gsymbol"])
if len(gene_symbols) > 0 and gene_symbols[0] != "NA":
gene_symbol = ",".join(gene_symbols)
gene_rec.attributes["ensg_id"] = [ensgene_id]
gene_rec.attributes["refseq_id"] = [refseq_id]
gene_rec.attributes["gsymbol"] = [gene_symbol]
# Yield all the gene's records
for g in gene_recs:
yield g
def output_filtered_comparisons(
self,
output_dir=None,
sort_column="bayes_factor",
columns_to_write=[ #"event_name",
"gene_id", "gene_symbol", "sample1_posterior_mean",
"sample1_ci_low", "sample1_ci_high", "sample2_posterior_mean",
"sample2_ci_low", "sample2_ci_high", "diff", "bayes_factor",
"isoforms", "sample1_counts", "sample1_assigned_counts",
"sample2_counts", "sample2_assigned_counts", "chrom", "strand",
"mRNA_starts", "mRNA_ends"
]):
"""
Output filtered comparisons table.
"""
if output_dir == None:
output_dir = self.misowrap_obj.comparisons_dir
# Output each file by event type
output_dir = os.path.join(output_dir, "filtered_events")
print "Outputting filtered events..."
print " - Output dir: %s" % (output_dir)
utils.make_dir(output_dir)
for event_type, filtered_df in self.filtered_events.iteritems():
curr_output_dir = os.path.join(output_dir, event_type)
print "Event type: %s" % (event_type)
# View by comparison
comparison_labels = \
utils.unique_list(filtered_df.index.get_level_values(0))
print "Outputting %d comparisons" % (len(comparison_labels))
for label in comparison_labels:
print "Comparison: %s" % (label)
comparison_output_dir = os.path.join(curr_output_dir, label)
utils.make_dir(comparison_output_dir)
output_filename = os.path.join(comparison_output_dir,
"%s.%s.filtered.miso_bf" \
%(label,
event_type))
print "Outputting to: %s" % (output_filename)
curr_df = filtered_df.ix[label].sort_index(by=sort_column,
ascending=False)
curr_df.to_csv(output_filename,
sep=self.delimiter,
float_format="%.4f",
cols=columns_to_write)
