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|
#!/bin/env python3
from flask import Flask, render_template, request, session, Response, redirect, url_for, flash
from flask_sqlalchemy import SQLAlchemy
import json
import shutil
from flask import jsonify
from datetime import datetime
import bcrypt
import tempfile
import random
import string
from ratspub import *
import time
import os
import re
import pytz
from os import listdir
import nltk
from nltk.corpus import stopwords
from nltk.stem.porter import PorterStemmer
from collections import Counter
import numpy as np
from numpy import array
import tensorflow
import keras
from keras.models import Model
from keras.preprocessing.text import Tokenizer
from keras.preprocessing.sequence import pad_sequences
from keras.layers import *
from keras.models import Sequential
from keras.layers import Dense
from keras.layers import Flatten
from keras.layers import Embedding
from keras import metrics
from keras import optimizers
import pickle
app=Flask(__name__)
datadir="/export/ratspub/"
app.config['SECRET_KEY'] = '#DtfrL98G5t1dC*4'
app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:///'+datadir+'userspub.sqlite'
db = SQLAlchemy(app)
nltk.data.path.append("./nlp/")
# the sqlite database
class users(db.Model):
__tablename__='user'
id = db.Column(db.Integer, primary_key=True)
name = db.Column(db.String(80), nullable=False)
email = db.Column(db.String(80), unique=True, nullable=False)
password = db.Column(db.String(128), nullable=False)
date_created = db.Column(db.DateTime, default=datetime.utcnow)
def clean_doc(doc, vocab):
doc = doc.lower()
tokens = doc.split()
re_punc = re.compile('[%s]' % re.escape(string.punctuation))
tokens = [re_punc.sub('' , w) for w in tokens]
tokens = [word for word in tokens if len(word) > 1]
stop_words = set(stopwords.words('english'))
tokens = [w for w in tokens if not w in stop_words]
porter = PorterStemmer()
stemmed = [porter.stem(word) for word in tokens]
return tokens
# load tokenizer
with open('./nlp/tokenizer.pickle', 'rb') as handle:
tokenizer = pickle.load(handle)
# load vocabulary
with open('./nlp/vocabulary.txt', 'r') as vocab:
vocab = vocab.read()
# create the CNN model
def create_model(vocab_size, max_length):
model = Sequential()
model.add(Embedding(vocab_size, 32, input_length=max_length))
model.add(Conv1D(filters=16, kernel_size=4, activation='relu'))
model.add(MaxPooling1D(pool_size=2))
model.add(Flatten())
model.add(Dense(10, activation='relu'))
model.add(Dense(1, activation='sigmoid'))
opt = keras.optimizers.Adamax(learning_rate=0.002, beta_1=0.9, beta_2=0.999)
model.compile(loss='binary_crossentropy', optimizer=opt, metrics=[keras.metrics.AUC()])
return model
@app.route("/")
def root():
return render_template('index.html')
@app.route("/login", methods=["POST", "GET"])
def login():
email = None
if request.method == "POST":
email = request.form['email']
password = request.form['password']
found_user = users.query.filter_by(email=email).first()
if (found_user and (bcrypt.checkpw(password.encode('utf8'), found_user.password))):
session['email'] = found_user.email
session['name'] = found_user.name
session['id'] = found_user.id
else:
flash("Invalid username or password!", "loginout")
return render_template('signup.html')
flash("Login Succesful!", "loginout")
return render_template('index.html')
@app.route("/signup", methods=["POST", "GET"])
def signup():
if request.method == "POST":
name = request.form['name']
email = request.form['email']
password = request.form['password']
found_user = users.query.filter_by(email=email).first()
if (found_user and (bcrypt.checkpw(password.encode('utf8'), found_user.password)==False)):
flash("Already registered, but wrong password!", "loginout")
return render_template('signup.html')
session['email'] = email
session['name'] = name
password = bcrypt.hashpw(password.encode('utf8'), bcrypt.gensalt())
user = users(name=name, email=email, password = password)
if found_user:
session['email'] = found_user.email
session['id'] = found_user.id
found_user.name = name
db.session.commit()
else:
db.session.add(user)
db.session.commit()
newuser = users.query.filter_by(email=session['email']).first()
session['id'] = newuser.id
flash("Login Succesful!", "loginout")
return render_template('index.html')
else:
if 'email' in session:
flash("Already Logged In!")
return render_template('index.html')
return render_template('signup.html')
@app.route("/signin", methods=["POST", "GET"])
def signin():
email = None
if request.method == "POST":
email = request.form['email']
password = request.form['password']
found_user = users.query.filter_by(email=email).first()
if (found_user and (bcrypt.checkpw(password.encode('utf8'), found_user.password))):
session['email'] = found_user.email
session['name'] = found_user.name
session['id'] = found_user.id
flash("Login Succesful!", "loginout")
return render_template('index.html')
else:
flash("Invalid username or password!", "loginout")
return render_template('signup.html')
return render_template('signin.html')
# change password
@app.route("/<nm_passwd>", methods=["POST", "GET"])
def profile(nm_passwd):
try:
if "_" in str(nm_passwd):
user_name = str(nm_passwd).split("_")[0]
user_passwd = str(nm_passwd).split("_")[1]
user_passwd = "b\'"+user_passwd+"\'"
found_user = users.query.filter_by(name=user_name).first()
if request.method == "POST":
password = request.form['password']
session['email'] = found_user.email
session['name'] = found_user.name
session['id'] = found_user.id
password = bcrypt.hashpw(password.encode('utf8'), bcrypt.gensalt())
found_user.password = password
db.session.commit()
flash("Your password is changed!", "loginout")
return render_template('index.html')
# remove reserved characters from the hashed passwords
reserved = (";", "/", "?", ":", "@", "=", "&", ".")
def replace_reserved(fullstring):
for replace_str in reserved:
fullstring = fullstring.replace(replace_str,"")
return fullstring
replaced_passwd = replace_reserved(str(found_user.password))
if replaced_passwd == user_passwd:
return render_template("/passwd_change.html", name=user_name)
else:
return "This url does not exist"
else:
return "This url does not exist"
except (AttributeError):
return "This url does not exist"
@app.route("/logout")
def logout():
if 'email' in session:
global user1
if session['name'] != '':
user1 = session['name']
else:
user1 = session['email']
flash("You have been logged out, {user1}", "loginout")
session.pop('email', None)
session.clear()
return render_template('index.html')
@app.route("/about")
def about():
return render_template('about.html')
@app.route('/progress')
def progress():
#get the type from checkbox
search_type = request.args.getlist('type')
if (search_type == []):
search_type = ['GWAS', 'function', 'addiction', 'drug', 'brain', 'stress', 'psychiatric']
session['search_type'] = search_type
# only 1-100 terms are allowed
genes=request.args.get('query')
genes=genes.replace(",", " ")
genes=genes.replace(";", " ")
genes=re.sub(r'\bLOC\d*?\b', "", genes, flags=re.I)
genes=genes.split()
if len(genes)>=100:
message="<span class='text-danger'>Up to 100 terms can be searched at a time</span>"
return render_template('index.html', message=message)
elif len(genes)==0:
message="<span class='text-danger'>Please enter a search term </span>"
return render_template('index.html', message=message)
tf_path=tempfile.gettempdir()
session['path']=tf_path+"/tmp" + ''.join(random.choice(string.ascii_letters) for x in range(6))
# put the query in session cookie
session['query']=genes
return render_template('progress.html', url_in="search", url_out="cytoscape")
@app.route("/search")
def search():
genes=session['query']
genes_for_folder_name =""
if len(genes) == 1:
marker = ""
genes_for_folder_name =str(genes[0])
elif len(genes) == 2:
marker = ""
genes_for_folder_name =str(genes[0])+"_"+str(genes[1])
elif len(genes) == 3:
marker = ""
genes_for_folder_name =str(genes[0])+"_"+str(genes[1])+"_"+str(genes[2])
else:
genes_for_folder_name =str(genes[0])+"_"+str(genes[1])+"_"+str(genes[2])
marker="_m"
# generate a unique session ID depending on timestamp to track the results
timestamp = datetime.utcnow().replace(microsecond=0)
timestamp = timestamp.replace(tzinfo=pytz.utc)
timestamp = timestamp.astimezone(pytz.timezone("America/Chicago"))
session['timestamp'] = timestamp
timeextension = str(timestamp)
timeextension = timeextension.replace(':', '_')
timeextension = timeextension.replace('-', '_')
timeextension = timeextension.replace(' ', '_')
timeextension = timeextension.replace('_06_00', '')
user_login=0
#create a folder for the search
if ('email' in session):
user_login=1
os.makedirs(datadir+"user/"+str(session['email']+"/"+timeextension+"_0_"+genes_for_folder_name+marker),exist_ok=True)
session['user_folder'] = datadir+"user/"+str(session['email'])
user_folder=session['user_folder']
session['path'] = datadir+"user/"+str(session['email'])+"/"+timeextension+"_0_"+genes_for_folder_name+marker+"/"+timeextension
percent=round(100/(len(genes)*6),1) # 6 categories
snt_file=session['path']+"_snt"
cysdata=open(session['path']+"_cy","w+")
sntdata=open(snt_file,"w+")
zeroLinkNode=open(session['path']+"_0link","w+")
search_type = session['search_type']
#consider the types got from checkbox
temp_nodes = ""
json_nodes = "{\"data\":["
if ("function" in search_type):
temp_nodes += n0
json_nodes += nj0
if ("addiction" in search_type):
temp_nodes += n1
json_nodes += nj1
if ("drug" in search_type):
temp_nodes += n2
json_nodes += nj2
if ("brain" in search_type):
temp_nodes += n3
json_nodes += nj3
if ("stress" in search_type):
temp_nodes += n4
json_nodes += nj4
if ("psychiatric" in search_type):
temp_nodes += n5
json_nodes += nj5
if ("GWAS" in search_type):
temp_nodes += n6
json_nodes += nj6
json_nodes = json_nodes[:-2]
json_nodes =json_nodes+"]}"
def generate(genes, tf_name):
sentences=str()
edges=str()
nodes = temp_nodes
progress=0
searchCnt=0
nodesToHide=str()
json_edges = str()
for gene in genes:
gene=gene.replace("-"," ")
# report progress immediately
progress+=percent
yield "data:"+str(progress)+"\n\n"
#addiction terms must present with at least one drug
addiction=undic(addiction_d) +") AND ("+undic(drug_d)
sent0=gene_category(gene, addiction_d, addiction, "addiction")
e0=generate_edges(sent0, tf_name)
ej0=generate_edges_json(sent0, tf_name)
# drug
drug=undic(drug_d)
sent1=gene_category(gene, drug_d, drug, "drug")
progress+=percent
yield "data:"+str(progress)+"\n\n"
e1=generate_edges(sent1, tf_name)
ej1=generate_edges_json(sent1, tf_name)
# function
function=undic(function_d)
sent2=gene_category(gene, function_d, function, "function")
progress+=percent
yield "data:"+str(progress)+"\n\n"
e2=generate_edges(sent2, tf_name)
ej2=generate_edges_json(sent2, tf_name)
# brain has its own query terms that does not include the many short acronyms
sent3=gene_category(gene, brain_d, brain_query_term, "brain")
progress+=percent
e3=generate_edges(sent3, tf_name)
ej3=generate_edges_json(sent3, tf_name)
# stress
stress=undic(stress_d)
sent4=gene_category(gene, stress_d, stress, "stress")
progress+=percent
yield "data:"+str(progress)+"\n\n"
e4=generate_edges(sent4, tf_name)
ej4=generate_edges_json(sent4, tf_name)
# psychiatric
psychiatric=undic(psychiatric_d)
sent5=gene_category(gene, psychiatric_d, psychiatric, "psychiatric")
progress+=percent
yield "data:"+str(progress)+"\n\n"
e5=generate_edges(sent5, tf_name)
ej5=generate_edges_json(sent5, tf_name)
# GWAS
e6=searchArchived('GWAS', gene, 'cys')
ej6=searchArchived('GWAS', gene , 'json')
#consider the types got from checkbox
geneEdges = ""
if ("addiction" in search_type):
geneEdges += e0
json_edges += ej0
if ("drug" in search_type):
geneEdges += e1
json_edges += ej1
if ("function" in search_type):
geneEdges += e2
json_edges += ej2
if ("brain" in search_type):
geneEdges += e3
json_edges += ej3
if ("stress" in search_type):
geneEdges += e4
json_edges += ej4
if ("psychiatric" in search_type):
geneEdges += e5
json_edges += ej5
if ("GWAS" in search_type):
geneEdges += e6
json_edges += ej6
## there is a bug here. zero link notes are not excluded anymore
if len(geneEdges) >1:
edges+=geneEdges
nodes+="{ data: { id: '" + gene + "', nodecolor:'#E74C3C', fontweight:700, url:'/startGeneGene?forTopGene="+gene+"'} },\n"
else:
nodesToHide+=gene + " "
sentences+=sent0+sent1+sent2+sent3+sent4+sent5
sent0=None
sent1=None
sent2=None
sent3=None
sent4=None
sent5=None
#save data before the last yield
searchCnt+=1
if (searchCnt==len(genes)):
progress=100
sntdata.write(sentences)
sntdata.close()
cysdata.write(nodes+edges)
cysdata.close()
zeroLinkNode.write(nodesToHide)
zeroLinkNode.close()
yield "data:"+str(progress)+"\n\n"
#edges in json format
json_edges="{\"data\":["+json_edges
json_edges = json_edges[:-2]
json_edges =json_edges+"]}"
#write edges to txt file in json format
with open(datadir+"edges.json", 'w') as edgesjson:
edgesjson.write(json_edges)
#write edges to txt file in json format also in user folder
if (user_login == 1):
with open(user_folder+"/"+timeextension+"_0_"+genes_for_folder_name+marker+"/edges.json", "w") as temp_file_edges:
temp_file_edges.write(json_edges)
#write nodes to txt file in json format
with open(datadir+"nodes.json", 'w') as nodesjson:
#if (userlogin) == 1:
nodesjson.write(json_nodes)
#write nodes to txt file in json format also in user folder
if ('email' in session):
with open(datadir+"user/"+str(session['email'])+"/"+timeextension+"_0_"+genes_for_folder_name+marker+"/nodes.json", "w") as temp_file_nodes:
temp_file_nodes.write(json_nodes)
return Response(generate(genes, snt_file), mimetype='text/event-stream')
@app.route("/tableview")
def tableview():
with open(datadir+"nodes.json") as jsonfile:
jnodes = json.load(jsonfile)
jedges =''
file_edges = open(datadir+'edges.json', 'r')
for line in file_edges.readlines():
if ':' not in line:
nodata_temp = 1
else:
nodata_temp = 0
with open(datadir+"edges.json") as edgesjsonfile:
jedges = json.load(edgesjsonfile)
break
genename=session['query']
if len(genename)>3:
genename = genename[0:3]
added = ",..."
else:
added = ""
gene_name = str(genename)[1:]
gene_name=gene_name[:-1]
gene_name=gene_name.replace("'","")
gene_name = gene_name+added
num_gene = gene_name.count(',')+1
message3="<b> Actions: </b><li> <font color=\"red\">Click on the abstract count to read sentences linking the keyword and the gene.</font> <li> Click on a gene to search its relations with top 200 addiction genes. <li> Click on a keyword to see the terms included in the search. <li>View the results in <a href='cytoscape'><b> a graph.</b></a>"
return render_template('tableview.html', nodata_temp=nodata_temp, num_gene=num_gene,session_path = session['path'], jedges=jedges, jnodes=jnodes,gene_name=gene_name, message3=message3)
@app.route("/tableview0")
def tableview0():
with open(datadir+"nodes.json") as jsonfile:
jnodes = json.load(jsonfile)
jedges =''
file_edges = open(datadir+'edges.json', 'r')
for line in file_edges.readlines():
if ':' not in line:
nodata_temp = 1
else:
nodata_temp = 0
with open(datadir+"edges.json") as edgesjsonfile:
jedges = json.load(edgesjsonfile)
break
genename=session['query']
if len(genename)>3:
genename = genename[0:3]
added = ",..."
else:
added = ""
gene_name = str(genename)[1:]
gene_name=gene_name[:-1]
gene_name=gene_name.replace("'","")
gene_name = gene_name+added
num_gene = gene_name.count(',')+1
message4="<b> Notes: </b><li> These are the keywords that have <b>zero</b> abstract counts. <li>View all the results in <a href='cytoscape'><b> a graph.</b></a>"
return render_template('tableview0.html',nodata_temp=nodata_temp, num_gene=num_gene,session_path = session['path'], jedges=jedges, jnodes=jnodes,gene_name=gene_name, message4=message4)
@app.route("/userarchive")
def userarchive():
if os.path.exists(datadir+"user/"+str(session['email'])) == False:
flash("Search history doesn't exist!")
return render_template('index.html')
if ('email' in session):
session['user_folder'] = datadir+"user/"+str(session['email'])
session_id=session['id']
def sorted_alphanumeric(data):
convert = lambda text: int(text) if text.isdigit() else text.lower()
alphanum_key = lambda key: [ convert(c) for c in re.split('([0-9]+)', key) ]
return sorted(data, key=alphanum_key)
dirlist = sorted_alphanumeric(os.listdir(session['user_folder']))
folder_list = []
directory_list = []
gene_list=[]
for filename in dirlist:
folder_list.append(filename)
gene_name = filename.split('_0_')[1]
if gene_name[-2:] == '_m':
gene_name = gene_name[:-2]
gene_name = gene_name + ", ..."
gene_name = gene_name.replace('_', ', ')
gene_list.append(gene_name)
gene_name=""
filename=filename[0:4]+"-"+filename[5:7]+"-"+filename[8:13]+":"+filename[14:16]+":"+filename[17:19]
directory_list.append(filename)
len_dir = len(directory_list)
message3="<b> Actions: </b><li> Click on the Date/Time to view archived results. <li>The Date/Time are based on US Central time zone. "
return render_template('userarchive.html', len_dir=len_dir, gene_list = gene_list, folder_list=folder_list, directory_list=directory_list, session_id=session_id, message3=message3)
# delete this search
@app.route('/remove', methods=['GET', 'POST'])
def remove():
remove_folder = request.args.get('remove_folder')
shutil.rmtree(datadir+"user/"+str(session['email']+"/"+remove_folder), ignore_errors=True)
return redirect(url_for('userarchive'))
@app.route('/date', methods=['GET', 'POST'])
def date():
select_date = request.args.get('selected_date')
#open the cache folder for the user
tf_path=datadir+"user"
if ('email' in session):
time_extension = str(select_date)
time_extension = time_extension.split('_0_')[0]
gene_name1 = str(select_date).split('_0_')[1]
time_extension = time_extension.replace(':', '_')
time_extension = time_extension.replace('-', '_')
session['path'] = tf_path+"/"+str(session['email'])+"/"+select_date+"/"+time_extension
session['user_folder'] = tf_path+"/"+str(session['email'])
else:
tf_path=tempfile.gettempdir()
session['path']=tf_path+"/tmp" + ''.join(random.choice(string.ascii_letters) for x in range(6))
with open(tf_path+"/"+str(session['email'])+"/"+select_date+"/edges.json", "r") as archive_file:
with open(datadir+"edges.json", "w") as temp_file:
for line in archive_file:
temp_file.write(line)
with open(tf_path+"/"+str(session['email'])+"/"+select_date+"/nodes.json", "r") as archive_file:
with open(datadir+"nodes.json", "w") as temp_file:
for line in archive_file:
temp_file.write(line)
with open(datadir+"nodes.json", "r") as jsonfile:
jnodes = json.load(jsonfile)
jedges =''
file_edges = open(datadir+'edges.json', 'r')
for line in file_edges.readlines():
if ':' not in line:
nodata_temp = 1
else:
nodata_temp = 0
with open(datadir+"edges.json") as edgesjsonfile:
jedges = json.load(edgesjsonfile)
break
gene_list=[]
if nodata_temp == 0:
for p in jedges['data']:
if p['source'] not in gene_list:
gene_list.append(p['source'])
if len(gene_list)>3:
gene_list = gene_list[0:3]
added = ",..."
else:
added = ""
gene_name = str(gene_list)[1:]
gene_name=gene_name[:-1]
gene_name=gene_name.replace("'","")
gene_name = gene_name+added
num_gene = gene_name.count(',')+1
else:
gene_name1 = gene_name1.replace("_", ", ")
gene_name = gene_name1
num_gene = gene_name1.count(',')+1
for i in range(0,num_gene):
gene_list.append(gene_name1.split(',')[i])
session['query'] = gene_list
message3="<b> Actions: </b><li><font color=\"red\">Click on the keywords to see the indicated number of abstracts </font><li> Click on a gene to search its relations with top 200 addiction genes<li>Click on a keyword to see the terms included in the search<li>Hover your pointer over a node to hide other links <li>Nodes can be moved around for better visibility, reload the page will restore the original layout<li> View the results in <a href='cytoscape'><b>a graph.</b></a>"
return render_template('tableview.html', title='',nodata_temp=nodata_temp, date=select_date, num_gene=num_gene,session_path = session['path'], jedges=jedges, jnodes=jnodes,gene_name=gene_name, message3=message3)
@app.route('/cytoscape')
def cytoscape():
message2="<b> Notes: </b><li><font color=\"red\">Click on a line to see the indicated number of abstracts </font> <li> Click on a gene to search its relations with top 200 addiction genes<li>Click on a keyword to see the terms included in the search<li>Hover your pointer over a node to hide other links <li>Nodes can be moved around for better visibility, reload the page will restore the original layout<li>View the results in <a href='tableview'><b>a table. </b></a>"
with open(session['path']+"_cy","r") as f:
elements=f.read()
with open(session['path']+"_0link","r") as z:
zeroLink=z.read()
if (len(zeroLink)>0):
message2+="<span style=\"color:darkred;\">No result was found for these genes: " + zeroLink + "</span>"
return render_template('cytoscape.html', elements=elements, message2=message2)
@app.route("/sentences")
def sentences():
def predict_sent(sent_for_pred):
max_length = 64
tokens = clean_doc(sent_for_pred, vocab)
tokens = [w for w in tokens if w in vocab]
# convert to line
line = ' '.join(tokens)
line = [line]
tokenized_sent = tokenizer.texts_to_sequences(line)
tokenized_sent = pad_sequences(tokenized_sent, maxlen=max_length, padding='post')
predict_sent = model.predict(tokenized_sent, verbose=0)
percent_sent = predict_sent[0,0]
if round(percent_sent) == 0:
return 'neg'
else:
return 'pos'
pmid_list=[]
edge=request.args.get('edgeID')
(tf_name, gene0, cat0)=edge.split("|")
if(cat0=='stress'):
model = create_model(23154, 64)
model.load_weights("./nlp/weights.ckpt")
out3=""
out_pos = ""
out_neg = ""
num_abstract = 0
stress_cellular = "<br><br><br>"+"</ol><b>Sentence(s) describing celluar stress (classified using a deep learning model):</b><hr><ol>"
stress_systemic = "<b>Sentence(s) describing systemic stress (classified using a deep learning model):</b><hr>"
with open(tf_name, "r") as df:
all_sents=df.read()
for sent in all_sents.split("\n"):
if len(sent.strip())!=0:
(gene,nouse,cat, pmid, text)=sent.split("\t")
if (gene.upper() == gene0.upper() and cat.upper() == cat0.upper()) :
out3+= "<li> "+ text + " <a href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=" + pmid +"\" target=_new>PMID:"+pmid+"<br></a>"
num_abstract += 1
if(pmid+cat0 not in pmid_list):
pmid_list.append(pmid+cat0)
if(cat0=='stress'):
out_pred = "<li> "+ text + " <a href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=" + pmid +"\" target=_new>PMID:"+pmid+"<br></a>"
out4 = predict_sent(text)
if(out4 == 'pos'):
out_pos += out_pred
else:
out_neg += out_pred
out1="<h3>"+gene0 + " and " + cat0 + "</h3>\n"
if len(pmid_list)>1:
out2 = str(num_abstract) + ' sentences in ' + str(len(pmid_list)) + ' studies' + "<br><br>"
else:
out2 = str(num_abstract) + ' sentence(s) in ' + str(len(pmid_list)) + ' study' "<br><br>"
if(out_neg == "" and out_pos == ""):
out= out1+ out2 +out3
elif(out_pos != "" and out_neg!=""):
out = out1 + out2 + stress_systemic+out_pos + stress_cellular + out_neg
elif(out_pos != "" and out_neg ==""):
out= out1+ out2 + stress_systemic + out_pos
elif(out_neg != "" and out_pos == ""):
out = out1 +out2+stress_cellular+out_neg
return render_template('sentences.html', sentences="<ol>"+out+"</ol><p>")
## show the cytoscape graph for one gene from the top gene list
@app.route("/showTopGene")
def showTopGene():
query=request.args.get('topGene')
nodesEdges=searchArchived('topGene',query, 'cys')
message2="<li><strong>"+query + "</strong> is one of the top addiction genes. <li> An archived search is shown. Click on the blue circle to update the results and include keywords for brain region and gene function. <strong> The update may take a long time to finish.</strong> "
return render_template("cytoscape.html", elements=nodesEdges, message="Top addiction genes", message2=message2)
@app.route("/shownode")
def shownode():
node=request.args.get('node')
allnodes={**brain_d, **drug_d, **function_d, **addiction_d, **stress_d, **psychiatric_d}
out="<p>"+node.upper()+"<hr><li>"+ allnodes[node].replace("|", "<li>")
return render_template('sentences.html', sentences=out+"<p>")
@app.route("/startGeneGene")
def startGeneGene():
session['forTopGene']=request.args.get('forTopGene')
return render_template('progress.html', url_in="searchGeneGene", url_out="showGeneTopGene")
@app.route("/searchGeneGene")
def gene_gene():
tmp_ggPMID=session['path']+"_ggPMID"
gg_file=session['path']+"_ggSent" #gene_gene
result_file=session['path']+"_ggResult"
def generate(query):
progress=1
yield "data:"+str(progress)+"\n\n"
os.system("esearch -db pubmed -query \"" + query + "\" | efetch -format uid |sort >" + tmp_ggPMID)
abstracts=os.popen("comm -1 -2 topGene_uniq.pmid " + tmp_ggPMID + " |fetch-pubmed -path "+pubmed_path+ " | xtract -pattern PubmedArticle -element MedlineCitation/PMID,ArticleTitle,AbstractText|sed \"s/-/ /g\"").read()
os.system("rm "+tmp_ggPMID)
#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()
progress=10
yield "data:"+str(progress)+"\n\n"
topGenes=dict()
out=str()
hitGenes=dict()
with open("topGene_symb_alias.txt", "r") as top_f:
for line in top_f:
(symb, alias)=line.strip().split("\t")
topGenes[symb]=alias.replace("; ","|")
allAbstracts= abstracts.split("\n")
abstractCnt=len(allAbstracts)
rowCnt=0
for row in allAbstracts:
rowCnt+=1
if rowCnt/10==int(rowCnt/10):
progress=10+round(rowCnt/abstractCnt,2)*80
yield "data:"+str(progress)+"\n\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:
if findWholeWord(query)(sent):
sent=re.sub(r'\b(%s)\b' % query, r'<strong>\1</strong>', sent, flags=re.I)
for symb in topGenes:
allNames=symb+"|"+topGenes[symb]
if findWholeWord(allNames)(sent) :
sent=sent.replace("<b>","").replace("</b>","")
sent=re.sub(r'\b(%s)\b' % allNames, r'<b>\1</b>', sent, flags=re.I)
out+=query+"\t"+"gene\t" + symb+"\t"+pmid+"\t"+sent+"\n"
if symb in hitGenes.keys():
hitGenes[symb]+=1
else:
hitGenes[symb]=1
progress=95
yield "data:"+str(progress)+"\n\n"
with open(gg_file, "w+") as gg:
gg.write(out)
gg.close()
results="<h4>"+query+" vs top addiction genes</h4> Click on the number of sentences will show those sentences. Click on the <span style=\"background-color:#FcF3cf\">top addiction genes</span> will show an archived search for that gene.<hr>"
topGeneHits={}
for key in hitGenes.keys():
url=gg_file+"|"+query+"|"+key
if hitGenes[key]==1:
sentword="sentence"
else:
sentword="sentences"
topGeneHits[ "<li> <a href=/sentences?edgeID=" + url+ " target=_new>" + "Show " + str(hitGenes[key]) + " " + sentword +" </a> about "+query+" and <a href=/showTopGene?topGene="+key+" target=_gene><span style=\"background-color:#FcF3cf\">"+key+"</span></a>" ]=hitGenes[key]
topSorted = [(k, topGeneHits[k]) for k in sorted(topGeneHits, key=topGeneHits.get, reverse=True)]
for k,v in topSorted:
results+=k
saveResult=open(result_file, "w+")
saveResult.write(results)
saveResult.close()
progress=100
yield "data:"+str(progress)+"\n\n"
## start the run
query=session['forTopGene']
return Response(generate(query), mimetype='text/event-stream')
@app.route('/showGeneTopGene')
def showGeneTopGene ():
with open(session['path']+"_ggResult", "r") as result_f:
results=result_f.read()
return render_template('sentences.html', sentences=results+"<p><br>")
## generate a page that lists all the top 150 addiction genes with links to cytoscape graph.
@app.route("/allTopGenes")
def top150genes():
return render_template("topAddictionGene.html")
if __name__ == '__main__':
db.create_all()
app.run(debug=True, port=4200)
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