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#!/usr/bin/env python3
import time
import ncbiutils
from Bio import Entrez
"""
Finds all rsids that are explicitly cited in pubmed
and returns a list
"""
def get_complete_rsids():
results = ncbiutils.db_query(db="snp",retmode="json",retmax=200000,retstart=0,term='snp_pubmed_cited[sb]')
rsidlist = results["esearchresult"]["idlist"]
for x in range(0, len(rsidlist)):
rsidlist[x] = "rs" + rsidlist[x]
return(rsidlist)
"""
Generates a list of PMIDs that are explicitly cite a given rsid
"""
def get_pmids(rsid):
searchterm = rsid + "+AND+pubmed_snp_cited[sb]"
print(searchterm)
results = ncbiutils.db_query(db="pubmed",retmode="json",retmax=200000,restart=0,term=searchterm, api_key="7c0213f7c513fa71fe2cb65b4dfefa76fb09")
pmidlist = results["esearchresult"]["idlist"]
print(pmidlist)
return(pmidlist)
"""
Takes the saved list of results from get_pmids and retrieves
the raw XML to parse. Currently goes article by article instead of
doing them in bulk. Could go either way. Unsure which way
is better / more efficient.
"""
def get_abstracts(results):
abstracts_list = []
for start in range(0, int(results["Count"]), 1):
# print("Going to download record %i to %i" % (start+1, end))
fetch_handle = Entrez.efetch(db="pubmed", rettype="abstract",
retmode="xml", retstart=start,
retmax=1,
webenv=results["WebEnv"],
query_key=results["QueryKey"])
data = fetch_handle.read()
fetch_handle.close()
root = ET.fromstring(data)
for abst in root.iter('Abstract'):
for sec in abst.iter('AbstractText'):
abstracts_list.append(sec.text)
print(abstracts_list)
return(abstracts_list)
def get_abstracts_from_list(pmids_list):
abstracts_list = []
for each_pmid in pmids_list:
fetch_handle = Entrez.efetch(db="pubmed", id=each_pmid, retmode='xml')
data = fetch_handle.read()
fetch_handle.close()
root = ET.fromstring(data)
for abst in root.iter('Abstract'):
for sec in abst.iter('AbstractText'):
abstracts_list.append(sec.text)
return(abstracts_list)
def main():
rsids = get_complete_rsids()
for rsid in rsids:
get_pmids(rsid)
return()
if __name__ == '__main__':
main()
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