def _process_pathway(cls, download_file, stage_output_file, section, source, is_public, config=None):
'''Function to parse the pathway input files eg: kegg, reactome, go
INPUT file format:
Pathway name \t Pathyway url \t List of entrez ids
REACTOME_RNA_POL_I_TRANSCRIPTION_TERMINATION
http://www.broadinstitute.org/gsea/msigdb/cards/REACTOME_RNA_POL_I_TRANSCRIPTION_TERMINATION1022
2068 2071 25885 284119 2965 2966 2967 2968 4331
The entrez ids are converted to ensembl ids and logs are written to track the conversion rates (LESS/MORE/EQUAL)
'''
json_target_file_path = stage_output_file.replace(".out", ".json")
json_target_file = open(json_target_file_path, mode='w', encoding='utf-8')
json_target_file.write('{"docs":[\n')
count = 0
tmp_row_count_file = open(download_file, encoding='utf-8')
row_count = sum(1 for row in tmp_row_count_file)
logger.debug('Number of lines in the file ' + str(row_count))
load_mapping = True
gene_sets = []
with open(download_file, encoding='utf-8') as csvfile:
reader = csv.reader(csvfile, delimiter='\t', quoting=csv.QUOTE_NONE)
for row in reader:
gene_sets.extend(row[2:])
csvfile.close()
ens_look_up = Gene._entrez_ensembl_lookup(gene_sets, section, config)
with open(download_file, encoding='utf-8') as csvfile:
reader = csv.reader(csvfile, delimiter='\t', quoting=csv.QUOTE_NONE)
for row in reader:
path_object = dict()
pathway_name = row[0]
pathway_url = row[1]
gene_sets = row[2:]
converted_genesets = [ens_look_up[entrez] for entrez in gene_sets if entrez in ens_look_up]
path_object["pathway_name"] = pathway_name
path_object["pathway_url"] = pathway_url
path_object["gene_sets"] = converted_genesets
path_object["source"] = source
path_object["is_public"] = is_public
json_target_file.write(json.dumps(path_object))
count += 1
if row_count == count:
json_target_file.write('\n')
else:
json_target_file.write(',\n')
json_target_file.write('\n]}')
logger.debug("No. genes to load "+str(count))
logger.debug("Json written to " + json_target_file_path)
logger.debug("Load mappings")
if load_mapping:
status = cls._load_pathway_mappings(section)
print(status)
def get_ensemb_ids(self, entrez_list):
config = {}
section = {}
section['index'] = 'genes_hg38_v0.0.2'
section['index_type'] = 'gene_history'
config['GENE_HISTORY'] = section
result_dict = Gene._entrez_ensembl_lookup(entrez_list, section, config)
return result_dict
def _process_bioplex(cls, download_file, stage_output_file, section, config):
'''Function to process bioplex data files. Interactors are in first two columns, they are converted to
ensembl ids and stored in temperory.out files
Input File format:
GeneA GeneB UniprotA UniprotB SymbolA SymbolB pW pNI pInt
100 728378 P00813 A5A3E0 ADA POTEF 2.38086E-09 0.000331856 0.999668142
100 345651 P00813 Q562R1 ADA ACTBL2 9.79E-18 0.211914437 0.788085563
Output file format:
interactorA interactorB
ENSG00000196839 ENSG00000196604
ENSG00000196839 ENSG00000169067
'''
stage_output_file_handler = open(stage_output_file, 'w')
mapped_counter = 0
unmapped_ids = []
stage_output_file_handler.write('interactorA' + '\t' + 'interactorB\n')
gene_sets = []
with open(download_file, encoding='utf-8') as csvfile:
reader = csv.DictReader(csvfile, delimiter='\t', quoting=csv.QUOTE_NONE)
for row in reader:
gene_sets.extend([row['GeneA'], row['GeneB']])
csvfile.close()
ens_look_up = Gene._entrez_ensembl_lookup(gene_sets, section, config)
with open(download_file, encoding='utf-8') as csvfile:
reader = csv.DictReader(csvfile, delimiter='\t', quoting=csv.QUOTE_NONE)
for row in reader:
interactor_a = row['GeneA']
interactor_b = row['GeneB']
if interactor_a in ens_look_up and interactor_b in ens_look_up:
line = ens_look_up[interactor_a] + '\t' + ens_look_up[interactor_b] + '\n'
stage_output_file_handler.write(line)
mapped_counter += 1
else:
line = interactor_a + '\t' + interactor_b + '\n'
unmapped_ids.append(interactor_a)
unmapped_ids.append(interactor_b)
logger.debug("\n".join(unmapped_ids))
logger.debug("Mapped {} Unmapped {} " . format(mapped_counter, len(unmapped_ids)))
stage_output_file_handler.close()
cls._process_interaction_out_file(stage_output_file, section, False)
