#!/bin/env python3 from nltk.tokenize import sent_tokenize import os import re from nltk.util import pr from addiction_keywords import * from gene_synonyms import * import ast from flask import session global pubmed_path def undic(dic): all_s='' for s in dic: all_s += "|".join(str(e) for e in s) all_s +="|" all_s=all_s[:-1] return all_s def findWholeWord(w): return re.compile(r'\b({0})\b'.format(w), flags=re.IGNORECASE).search def getabstracts(gene,query): if query[-1] =='s': query2 = query+"*" else: query2 = query+"s*" query3 = query2.replace("s|", "s* OR ") query4 = query3.replace("|", "s* OR ") #query4=query #query="\"(" + query4 + ") AND ((" + gene + "[tiab]) or (" + gene + "[meSH]))\"" query="\"(" + query4 + ") AND (" + gene + " [tiab])\"" #query = "neurons* AND (penk [tiab])" abstracts = os.popen("esearch -db pubmed -query " + query \ + " | efetch -format uid |fetch-pubmed -path "+ pubmed_path \ + " | xtract -pattern PubmedArticle -element MedlineCitation/PMID,ArticleTitle,AbstractText|sed \"s/-/ /g\"").read() #print(abstracts) return(abstracts) sentences_ls=[] def getSentences(gene, sentences_ls): out=str() # Keep the sentence only if it contains the gene #print(sentences_ls) for sent in sentences_ls: #if gene.lower() in sent.lower(): if re.search(r'\b'+gene.lower()+r'\b',sent.lower()): pmid = sent.split(' ')[0] sent = sent.split(' ',1)[1] sent=re.sub(r'\b(%s)\b' % gene, r'\1', sent, flags=re.I) out+=pmid+"\t"+sent+"\n" return(out) def gene_category(gene, cat_d, cat, abstracts,addiction_flag,dictn): # e.g. BDNF, addiction_d, undic(addiction_d) "addiction" sents=getSentences(gene, abstracts) #print(abstracts) out=str() if (addiction_flag==1): for sent in sents.split("\n"): for key in cat_d: if key =='s': key_ad = key+"*" else: key_ad = key+"s*" if findWholeWord(key_ad)(sent) : sent=sent.replace("","").replace("","") # remove other highlights sent=re.sub(r'\b(%s)\b' % key_ad, r'\1', sent, flags=re.I) # highlight keyword out+=gene+"\t"+ cat + "\t"+key+"\t"+sent+"\n" else: for key_1 in dictn[cat_d].keys(): for key_2 in dictn[cat_d][key_1]: if key_2[-1] =='s': key_2 = key_2+"*" else: key_2 = key_2+"s*" for sent in sents.split("\n"): if findWholeWord(key_2)(sent) : sent=sent.replace("","").replace("","") # remove other highlights sent=re.sub(r'\b(%s)\b' % key_2, r'\1', sent, flags=re.I) # highlight keyword out+=gene+"\t"+ cat + "\t"+key_1+"\t"+sent+"\n" return(out) def generate_nodes(nodes_d, nodetype,nodecolor): # Include all search terms even if there are no edges, just to show negative result json0 =str() for node in nodes_d: json0 += "{ data: { id: '" + node + "', nodecolor: '" + nodecolor + "', nodetype: '"+nodetype + "', url:'/shownode?nodetype=" + nodetype + "&node="+node+"' } },\n" return(json0) def generate_nodes_json(nodes_d, nodetype,nodecolor): # Include all search terms even if there are no edges, just to show negative result nodes_json0 =str() for node in nodes_d: nodes_json0 += "{ \"id\": \"" + node + "\", \"nodecolor\": \"" + nodecolor + "\", \"nodetype\": \"" + nodetype + "\", \"url\":\"/shownode?nodetype=" + nodetype + "&node="+node+"\" },\n" return(nodes_json0) def generate_edges(data, filename): pmid_list=[] json0=str() edgeCnts={} for line in data.split("\n"): if len(line.strip())!=0: (source, cat, target, pmid, sent) = line.split("\t") edgeID=filename+"|"+source+"|"+target if (edgeID in edgeCnts) and (pmid+target not in pmid_list): edgeCnts[edgeID]+=1 pmid_list.append(pmid+target) elif (edgeID not in edgeCnts) and (pmid+target not in pmid_list): edgeCnts[edgeID]=1 pmid_list.append(pmid+target) for edgeID in edgeCnts: (filename, source,target)=edgeID.split("|") json0+="{ data: { id: '" + edgeID + "', source: '" + source + "', target: '" + target + "', sentCnt: " + str(edgeCnts[edgeID]) + ", url:'/sentences?edgeID=" + edgeID + "' } },\n" return(json0) def generate_edges_json(data, filename): pmid_list=[] edges_json0=str() edgeCnts={} for line in data.split("\n"): if len(line.strip())!=0: (source, cat, target, pmid, sent) = line.split("\t") edgeID=filename+"|"+source+"|"+target if (edgeID in edgeCnts) and (pmid+target not in pmid_list): edgeCnts[edgeID]+=1 pmid_list.append(pmid+target) elif (edgeID not in edgeCnts) and (pmid+target not in pmid_list): edgeCnts[edgeID]=1 pmid_list.append(pmid+target) for edgeID in edgeCnts: (filename, source,target)=edgeID.split("|") edges_json0+="{ \"id\": \"" + edgeID + "\", \"source\": \"" + source + "\", \"target\": \"" + target + "\", \"sentCnt\": \"" + str(edgeCnts[edgeID]) + "\", \"url\":\"/sentences?edgeID=" + edgeID + "\" },\n" return(edges_json0) def searchArchived(sets, query, filetype,sents, path_user): if sets=='topGene': dataFile="topGene_addiction_sentences.tab" nodes= "{ data: { id: '" + query + "', nodecolor: '" + "#2471A3" + "', fontweight:700, url:'/progress?query="+query+"' } },\n" elif sets=='GWAS': dataFile="gwas_addiction.tab" nodes=str() pmid_list=[] catCnt={} sn_file = '' for sn in sents: (symb, cat0, cat1, pmid, sent)=sn.split("\t") if (symb.upper() == query.upper()) : if (cat1 in catCnt.keys()) and (pmid+cat1 not in pmid_list): pmid_list.append(pmid+cat1) catCnt[cat1]+=1 elif (cat1 not in catCnt.keys()): catCnt[cat1]=1 pmid_list.append(pmid+cat1) sn_file += sn + '\n' nodes= "{ data: { id: '" + query + "', nodecolor: '" + "#2471A3" + "', fontweight:700, url:'/progress?query="+query+"' } },\n" edges=str() gwas_json=str() nodecolor={} nodecolor["GWAS"]="hsl(0, 0%, 70%)" for key in catCnt.keys(): if sets=='GWAS': nc=nodecolor["GWAS"] nodes += "{ data: { id: '" + key + "', nodecolor: '" + nc + "', url:'https://www.ebi.ac.uk/gwas/search?query="+key.replace("_GWAS","")+"' } },\n" edgeID=path_user+'gwas_results.tab'+"|"+query+"|"+key edges+="{ data: { id: '" + edgeID+ "', source: '" + query + "', target: '" + key + "', sentCnt: " + str(catCnt[key]) + ", url:'/sentences?edgeID=" + edgeID + "' } },\n" gwas_json+="{ \"id\": \"" + edgeID + "\", \"source\": \"" + query + "\", \"target\": \"" + key + "\", \"sentCnt\": \"" + str(catCnt[key]) + "\", \"url\":\"/sentences?edgeID=" + edgeID + "\" },\n" return(nodes+edges,gwas_json,sn_file) pubmed_path=os.environ["EDIRECT_PUBMED_MASTER"]