Initial commit

gnomad_python_api.py

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+# gnomAD Python API by @furkanmtorun 
+# [[email protected]](mailto:[email protected]) 
+# | GitHub: [@furkanmtorun](https://github.com/furkanmtorun) 
+# | [Google Scholar](https://scholar.google.com/citations?user=d5ZyOZ4AAAAJ) 
+# | [Personal Website](https://furkanmtorun.github.io/)
+
+# Import required libraries and packages
+from pandas.io.json import json_normalize as json_normalize
+from tqdm import tqdm
+import pandas as pd
+import requests
+import argparse
+import json
+import os
+
+# Create a folder for outputs in the current directory
+if not os.path.exists('outputs/'):
+ os.mkdir('outputs/')
+
+# Argument parsing
+def arg_parser():
+ global filter_by
+ global search_by
+ global dataset
+ parser = argparse.ArgumentParser()
+ parser.add_argument("-filter_by", type=str, required=True, default="gene_name", help="Get your variants according to: gene_name, gene_id or transcript_id ")
+ parser.add_argument("-search_by", type=str, required=True, default="TP53", help="Type the Ensembl Gene ID or Gene Name or the file name (e.g: myGenes.txt) containing genes")
+ parser.add_argument("-dataset", type=str, required=True, default="gnomad_r2_1", help="Select your dataset: exac, gnomad_r2_1, gnomad_r3, gnomad_r2_1_controls, gnomad_r2_1_non_neuro, gnomad_r2_1_non_cancer, gnomad_r2_1_non_topmed")
+ args = parser.parse_args()
+ if args.dataset not in ["exac", "gnomad_r2_1", "gnomad_r3", "gnomad_r2_1_controls", "gnomad_r2_1_non_neuro", "gnomad_r2_1_non_cancer", "gnomad_r2_1_non_topmed"]:
+ print("! Select a proper gnomAD data set:\n\texac, gnomad_r2_1, gnomad_r3, gnomad_r2_1_controls, gnomad_r2_1_non_neuro, gnomad_r2_1_non_cancer, gnomad_r2_1_non_topmed")
+ if args.filter_by not in ["gene_name", "gene_id", "transcript_id"]:
+ print("! Select a proper filter type :\n\tgene_name, gene_id or transcript_id")
+ filter_by = args.filter_by
+ search_by = args.search_by
+ dataset = args.dataset
+
+# gnomAD Parameters and API Function
+end_point = "https://gnomad.broadinstitute.org/api/"
+
+def get_variants_by(filter_by, search_term, dataset, timeout=None):
+ query = """
+ {
+ %s(%s: "%s") {
+ variants(dataset: %s) {
+ gene_id
+ gene_symbol
+ chrom
+ pos
+ rsid
+ ref
+ alt
+ consequence
+ genome {
+ genome_af:af
+ genome_ac:ac
+ genome_an:an
+ genome_ac_hemi:ac_hemi
+ genome_ac_hom:ac_hom
+ }
+ exome {
+ exome_af:af
+ exome_ac:ac
+ exome_an:an
+ exome_ac_hemi:ac_hemi
+ exome_ac_hom:ac_hom
+ }
+ flags
+ lof
+ consequence_in_canonical_transcript
+ gene_symbol
+ hgvsc
+ lof_filter
+ lof_flags
+ hgvsc
+ hgvsp
+ reference_genome
+ variant_id: variantId
+ }
+ }
+ }
+ """
+ if filter_by == "transcript_id":
+ query = query % ("transcript", filter_by, search_term, dataset)
+ else:
+ query = query % ("gene", filter_by, search_term, dataset)
+ response = requests.post(end_point, data={'query': query}, timeout=timeout)
+ if response.status_code == 200:
+ try:
+ if filter_by == "transcript_id":
+ data = json_normalize(response.json()["data"]["transcript"]["variants"])
+ else:
+ data = json_normalize(response.json()["data"]["gene"]["variants"])
+ data.columns = data.columns.map(lambda x: x.split(".")[-1])
+ data.to_csv("outputs/" + search_term + ".tsv", sep="\t", index=False) 
+ # return data
+ except (KeyError, TypeError):
+ print(str(response["error"]))
+ except (ConnectionError, ConnectionAbortedError, ConnectionRefusedError, ConnectionResetError):
+ print("An unknown error occured regarding the internet connection!")
+ elif response.status_code == 404:
+ print('API is not accessible right now. Check the end point out!')
+
+# Action
+if __name__ == "__main__":
+ arg_parser()
+ if "." in search_by.upper():
+ try:
+ with open(search_by, "r") as f:
+ gene_list = [line.rstrip() for line in f]
+ for tmp_gene in tqdm(gene_list):
+ get_variants_by(filter_by, tmp_gene.upper(), dataset)
+ except:
+ print("A problem occured while reading the file namely {} or the type {} you selected is wrong!"\
+ .format(search_by, filter_by))
+ finally:
+ f.close()
+ elif "." not in search_by.upper():
+ get_variants_by(filter_by, search_by.upper(), dataset)

requirements.txt

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+pandas
+requests
+tqdm
+argparse