From 35a5303bd958313d92323b4187ae67c950417125 Mon Sep 17 00:00:00 2001
From: Hao Chen
Date: Mon, 6 May 2019 08:17:25 -0500
Subject: initial commit

---
 get_addiction_sentences.py | 83 ++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 83 insertions(+)
 create mode 100644 get_addiction_sentences.py

(limited to 'get_addiction_sentences.py')

diff --git a/get_addiction_sentences.py b/get_addiction_sentences.py
new file mode 100644
index 0000000..30a8e50
--- /dev/null
+++ b/get_addiction_sentences.py
@@ -0,0 +1,83 @@
+#!/bin/env python3 
+from nltk.tokenize import sent_tokenize
+import os
+import re
+import codecs
+import sys
+
+gene=sys.argv[1]
+
+addiction_terms="sensitization|intake|addiction|drug abuse|relapse|self-administered|self-administration|voluntary|reinstatement|binge|intoxication|withdrawal|chronic"
+
+drugs="alcohol|alcoholism|smoking|nicotine|tobacco|methamphetamine|amphetamine|cocaine|opioid|fentanyl|oxycodone|oxycontin|heroin|morphine|marijuana|cannabinoid|tetrahydrocannabinol|thc"
+
+brain_regions="cortex|accumbens|striatum|amygadala|hippocampus|tegmental|mesolimbic|infralimbic|prelimbic"
+
+brain_d ={"cortex":"cortex|pfc|vmpfc|il|pl|prelimbic|infralimbic",
+          "striatum":"striatum|STR",
+          "accumbens":"shell|core|NAcc|acbs|acbc",
+          "hippocampus":"hippocampus|hipp|hip|ca1|ca3|dentate|gyrus",
+          "amygadala":"amygadala|cea|bla|amy",
+          "ventral tegmental":"ventral tegmental|vta"
+          }
+
+function="LTP|LTD|plasticity|regulate|glutamate|GABA|cholinergic|serotoninergic|synaptic|methylation|transcription|phosphorylation"
+
+drugs_d = {"alcohol":"alcohol|alcoholism",
+        "nicotine":"smoking|nicotine|tobacco",
+        "amphetamine":"methamphetamine|amphetamine",
+        "cocaine":"cocaine",
+        "opioid":"opioid|fentanyl|oxycodone|oxycontin|heroin|morphine",
+        "cannabinoid":"marijuana|cannabinoid|Tetrahydrocannabinol|thc"
+        }
+
+def findWholeWord(w):
+    return re.compile(r'\b({0})\b'.format(w), flags=re.IGNORECASE).search
+
+def getSentences(query):
+    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").read()
+    out=str()
+    for row in abstracts.split("\n"):
+        tiab=row.split("\t")
+        pmid = tiab.pop(0)
+        tiab= " ".join(tiab)
+        sentences = sent_tokenize(tiab)
+        for sent in sentences:
+            if findWholeWord(gene)(sent):
+                sent=re.sub(r'\b(%s)\b' % gene, r'<b>\1</b>', sent, flags=re.I)
+                out+=pmid+"\t"+sent+"\n"
+    return(out)
+
+def gene_addiction(gene):
+    q="\"(" + addiction_terms.replace("|", " OR ")  + ") AND (" + drugs.replace("|", " OR ", ) + ") AND " + gene + "\""
+    sents=getSentences(q)
+    out=str()
+    for sent in sents.split("\n"):
+        for drug0 in drugs_d:
+            if findWholeWord(drugs_d[drug0])(sent) :
+                sent=re.sub(r'\b(%s)\b' % drugs_d[drug0], r'<b>\1</b>', sent, flags=re.I)
+                out+=gene+"\t"+drug0+"\t"+sent+"\n"
+    return(out)
+
+def gene_brainRegion(gene):
+    q="\"(" + brain_regions.replace("|", " OR ")  + ") AND " + gene + "\""
+    sents=getSentences(q)
+    out=str()
+    for sent in sents.split("\n"):
+        for brain0 in brain_d:
+            if findWholeWord(brain_d[brain0])(sent) :
+                sent=re.sub(r'\b(%s)\b' % brain_d[brain0], r'<b>\1</b>', sent, flags=re.I)
+                out+=gene+"\t"+brain0+"\t"+sent+"\n"
+    return(out)
+
+report=str()
+out=gene_addiction(gene)
+report+=out
+out=gene_brainRegion(gene)
+report+=out
+with codecs.open(gene+"_addiction_sentences.tab", "w", encoding='utf8') as writer:
+   writer.write(report)
+   writer.close()
+
+
+
-- 
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