From a5d68f2bb80b89a8a6cf1051754112eda70316df Mon Sep 17 00:00:00 2001
From: Hao Chen
Date: Sun, 19 May 2019 13:19:46 -0500
Subject: clean up
---
cnt_gene_addiction_abstracts.py | 34 -
stop_words_addiction_gene_search.txt | 1430 +
templates/about.html | 4 +-
topGene_step4_get_pmids_for_all_top_genes.py | 2 +-
top_150_addiction_genes_uniq.pmid | 1443666 -----------------------
5 files changed, 1433 insertions(+), 1443703 deletions(-)
delete mode 100755 cnt_gene_addiction_abstracts.py
create mode 100644 stop_words_addiction_gene_search.txt
delete mode 100644 top_150_addiction_genes_uniq.pmid
diff --git a/cnt_gene_addiction_abstracts.py b/cnt_gene_addiction_abstracts.py
deleted file mode 100755
index f55586f..0000000
--- a/cnt_gene_addiction_abstracts.py
+++ /dev/null
@@ -1,34 +0,0 @@
-#!/bin/env python3
-import os
-import re
-import time
-from ratspub import *
-## turn dictionary (synonyms) to regular expression
-
-def gene_addiction_cnt(gene):
- q="\"(" + addiction.replace("|", "[tiab] OR ") + ") AND (" + drug.replace("|", "[tiab] OR ", ) + ") AND (" + gene + ")\""
- count=os.popen('esearch -db pubmed -query ' + q + ' | xtract -pattern ENTREZ_DIRECT -element Count ').read()
- if (len(count)==0):
- print("pause")
- time.sleep(15)
- gene_addiction_cnt(gene)
- return (count)
-
-out=open("gene_addiction_cnt_result_part1.tab", "w+")
-
-cnt=0
-with open ("./ncbi_gene_symb_syno_txid9606_part1.txt", "r") as f:
- for line in f:
- line=re.sub(r"\)|\(|\[|\]|\*|\'","",line)
- (gene, synoms)=line.strip().split("\t")
- if (gene[0:3] != "LOC"):
- cnt+=1
- for syno in synoms.split("|"):
- if len(syno)>3:
- gene+="|"+syno
- gene_q=gene.replace("|", " [tiab] OR ")
- gene_q+="[tiab]"
- count=gene_addiction_cnt(gene_q)
- print(gene+"\t"+count)
- out.write(gene+"\t"+count)
-
diff --git a/stop_words_addiction_gene_search.txt b/stop_words_addiction_gene_search.txt
new file mode 100644
index 0000000..01a5eae
--- /dev/null
+++ b/stop_words_addiction_gene_search.txt
@@ -0,0 +1,1430 @@
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+SAO
+WD1
+xxERP
+YRS
+PCS
+ZIP
+UTR
+xxNODAL
+UP 1
+GALPHA
+ARCH
+xxPROC
+xxMIP
+xxSNAP
+xxSTAT
+CD14
+xxWARS
+ACPA
+SIDS
+xxECT
+xxMYOSIN
+xxGLYT1
+GNTI
+xxCBS
+xxBEAN1
+xxADM
+AFRO
+CREST
+xxOTP
+xxGPT
+xxECD
+SAPS
+PREP
+INDO
+xxDAP
+CPAP
+xxOX2R
+xxHAP1
+xxPREP
+DASS
+xxKRAS
+xxGRIN1
+xxFTCD
+FLIP
diff --git a/templates/about.html b/templates/about.html
index e9185a9..4ea4112 100644
--- a/templates/about.html
+++ b/templates/about.html
@@ -8,9 +8,9 @@
These gene-keyword relationships are presented as an interactive cytoscape graph.
-
Clicking the links will bring up the corresponding sentences in a new browser window. Clicking the keyword nodes will bring up all the terms included. Clicking on the gene nodes will start a new search to find sentences containing that gene and the top 150 addiction genes.
+
Clicking the links will bring up the corresponding sentences in a new browser window. Clicking the keyword nodes will bring up all the terms included. Clicking on the gene nodes will start a new search to find sentences containing that gene and the top 200 addiction genes.
-
The top 150 addiction genes were obtained by searching All human genes against addiction related keywords. The archived results for these top addiction genes can be accessed via the Addiction Genes link.
+
The top 200 addiction genes were obtained by searching All human genes against addiction related keywords. The archived results for these top addiction genes can be accessed via the Addiction Genes link.
Source code