find top genes

1 files changed, 59 insertions, 0 deletions

diff --git a/topGene_step2_cnt_sentences.py b/topGene_step2_cnt_sentences.py
new file mode 100755
index 0000000..fe97cdd
--- /dev/null
+++ b/topGene_step2_cnt_sentences.py
@@ -0,0 +1,59 @@
+#!/bin/env python3 
+import os
+import re
+import time
+from nltk.tokenize import sent_tokenize
+from ratspub_keywords import *
+
+def undic(dic):
+    return "|".join(dic.values())
+
+def findWholeWord(w):
+    return re.compile(r'\b({0})\b'.format(w), flags=re.IGNORECASE).search
+
+def getSentences(query, genes):
+    abstracts = os.popen("esearch -db pubmed -query " +  query + " | efetch -format uid |fetch-pubmed -path /run/media/hao/PubMed/Archive/ | xtract -pattern PubmedArticle -element MedlineCitation/PMID,ArticleTitle,AbstractText|sed \"s/-/ /g\"").read()
+    gene_syno=genes.split("|")
+    symb=gene_syno[0]
+    out=str()
+    for row in abstracts.split("\n"):
+        tiab=row.split("\t")
+        pmid = tiab.pop(0)
+        tiab= " ".join(tiab)
+        sentences = sent_tokenize(tiab)
+          ## keep the sentence only if it contains the gene 
+        for sent in sentences:
+            for gene in gene_syno:
+                if findWholeWord(gene)(sent):
+                    sent=re.sub(r'\b(%s)\b' % gene, r'<strong>\1</strong>', sent, flags=re.I)
+                    for drug0 in drug_d:
+                        if findWholeWord(drug_d[drug0])(sent) :
+                            sent=sent.replace("<b>","").replace("</b>","")
+                            sent=re.sub(r'\b(%s)\b' % drug_d[drug0], r'<b>\1</b>', sent, flags=re.I)
+                            out+=symb+"\t"+"drug\t" + drug0+"\t"+pmid+"\t"+sent+"\n"
+                    for add0 in addiction_d:
+                        if findWholeWord(addiction_d[add0])(sent) :
+                            sent=sent.replace("<b>","").replace("</b>","")
+                            sent=re.sub(r'\b(%s)\b' % addiction_d[add0], r'<b>\1</b>', sent, flags=re.I)
+                            out+=symb+"\t"+"addiction\t"+add0+"\t"+pmid+"\t"+sent+"\n"
+    return(out)
+
+addiction=undic(addiction_d)
+drug=undic(drug_d)
+
+
+out=open("gene_addiction_sentences.tab", "w+")
+cnt=0
+with open ("./ncbi_gene_symb_syno_name_txid9606_absCnt_sorted_absCnt_sorted_absCnt_sorted.txt", "r") as f:
+    for line in f:
+        (genes, abstractCount)=line.strip().split("\t")
+        if int(abstractCount)>20:
+            symb=genes.split("|")[0]
+            print(symb+"-->"+genes)
+            q="\'(\"" + addiction.replace("|", "\"[tiab] OR \"")  + "\") AND (\"" + drug.replace("|", "\"[tiab] OR \"", ) + "\") AND (\"" + genes.replace("|", "\"[tiab] OR \"", ) + "\")\'"
+            sentences=getSentences(q,genes)
+            out.write(sentences)
+out.close()
+
+os.system("cut -f 1,4 gene_addiction_sentences.tab |uniq  |cut -f 1 |uniq -c |sort -rn > topGeneAbstractCount.tab")
+