def annotate_and_output_results(g_patient, g_reference, output_results):
import forannotation as ANNO
annotated_alterations = ANNO.alteration_list_to_transcrit_mutation(g_patient, g_reference)
# add experiment arguments
PROGRAMEND = time.time()
experiment_description = {}
this_timestamp = get_timestamp()
experiment_description['timestamp'] = this_timestamp
experiment_description['exec_time'] = PROGRAMEND - PROGRAMSTART
experiment_description['parameters'] = vars(args)
experiment_description['n_reads'] = g_patient.n_reads
experiment_description['git_revision_hash'] = get_git_revision_hash()
experiment_description['significant_alterations'] = annotated_alterations
experiment_description['graphs'] = {
"coverage_total": g_patient.coverage['total'],
"before_cleaning": len(g_patient.dbg),
"after_clearning": len(g_patient.dbgclean)
}
experiment_description['all_alterations'] = []
for x in g_patient.alteration_list:
alteration_description = x.__dict__
del alteration_description['reference_path']
del alteration_description['alternative_path']
del alteration_description['random_alternative_count_list']
del alteration_description['random_reference_count_list']
del alteration_description['random_ratio_list']
alteration_description['edit_operations'] = find_edit_operations(x.reference_sequence, x.alternative_sequence)
alteration_description['alignment'] = pairwise2.align.globalms(x.reference_sequence, x.alternative_sequence, 2, -3, -5, -2)[0]
experiment_description['all_alterations'].append(alteration_description)
print json.dumps(experiment_description)
if output_results:
with open(output_results, "w") as f:
json.dump(experiment_description, f)
def annotate_and_output_results(g_patient, g_reference, output_results):
import forannotation as ANNO
annotated_alterations = ANNO.alteration_list_to_transcrit_mutation(
g_patient, g_reference)
# add experiment arguments
PROGRAMEND = time.time()
experiment_description = {}
this_timestamp = get_timestamp()
experiment_description['timestamp'] = this_timestamp
experiment_description['exec_time'] = PROGRAMEND - PROGRAMSTART
experiment_description['parameters'] = vars(args)
experiment_description['n_reads'] = g_patient.n_reads
experiment_description['git_revision_hash'] = get_git_revision_hash()
# experiment_description['memory_usage'] = process.memory_info().rss
experiment_description['significant_alterations'] = annotated_alterations
experiment_description['graphs'] = {
"coverage_total": g_patient.coverage['total'],
"before_cleaning": len(g_patient.dbg),
"after_clearning": len(g_patient.dbgclean)
}
experiment_description['all_alterations'] = []
for x in g_patient.alteration_list:
alteration_description = x.__dict__
del alteration_description['reference_path']
del alteration_description['alternative_path']
del alteration_description['random_alternative_count_list']
del alteration_description['random_reference_count_list']
del alteration_description['random_ratio_list']
alteration_description['edit_operations'] = find_edit_operations(
x.reference_sequence, x.alternative_sequence)
alteration_description['alignment'] = pairwise2.align.globalms(
x.reference_sequence, x.alternative_sequence, 2, -3, -5, -2)[0]
experiment_description['all_alterations'].append(
alteration_description)
# print json.dumps(experiment_description)
if output_results:
with open(output_results, "w") as f:
json.dump(experiment_description, f)
def test_find_edit_operations(self): ref="CTGGGAGAGACCGGCGCACAGAGGAAGAGAATCTCCGCAAGAAAGGGGAGCCTCAC" alt="CTGGGAGAGACCGGCGCACAccGAGGAAGAGAATCTCcGCAAGAAAGGGGAGCCTCAC" print find_edit_operations(ref,alt)