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pazar_database.py
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pazar_database.py
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#!/usr/bin/env python
'''
Add the pazar database to the Neo4j graph database
'''
import glob, sys, time, re
from uniprot_queries import uniprot_queries
from graph_database import graph_database
from chebi_from_string import chebi_from_string
from brenda_annotation import brenda_annotation
class pazar_database():
def __init__(self, organism, neo4j, uniprot_query):
self.organism = organism
self.rel_dict = {}
self.neo4j = neo4j
self.uniprot_query = uniprot_query
self.information_dictio = {}
def get_data(self):
'''
Obtain all the files to be processed.
Carefull: The directories are harcodded.
Better not to move files/folders
'''
directory = './data/pazar_data/'
files = glob.glob(directory + '*')
return files
def fill_info_dict(self, protein, name, genes, proteins):
'''
Insert the information from the database
to get all the info from a protein
'''
if protein not in self.information_dictio.keys():
protList = []; geneList = []
for prot in proteins.split('('):
protList.append(re.sub('\)', '', prot).encode('utf8'))
for gene in genes.split():
geneList.append(re.sub(':', '', gene).encode('utf8'))
self.information_dictio[protein] = {'Entry':name, 'GeneNames':geneList, 'ProteinNames':protList}
return None
def process_files(self):
'''
Obtain the TF and target gene according to
the pazar DB files
'''
files = self.get_data()
#files = ['/home/salva/extract_path_neo4j/data/pazar_data/pazar_ABS_20120522.csv']
for file in files:
lines = [line for line in open(file) if self.organism in line]
for line in lines:
line = line.split('\t')
if line[8] == self.organism:
TF = line[2]; gene = line[4]
pmid = line[-2]; method = line[-1]
TFpage = self.uniprot_query.mapping_id(TF, 'ID')
TF = TFpage[0]; entry = TFpage[1]; genes = TFpage[2]; proteins = TFpage[3]
self.fill_info_dict(TF, entry, genes, proteins)
genePage = self.uniprot_query.mapping_id(gene, 'ENSEMBL_ID')
gene = genePage[0]; entry = genePage[1]; genes = genePage[2]; proteins = genePage[3]
self.fill_info_dict(gene, entry, genes, proteins)
if (TF != '' and gene != ''):
if TF not in self.rel_dict.keys():
self.rel_dict[TF] = {}
if gene in self.rel_dict[TF].keys():
self.rel_dict[TF][gene]['method'].add(method)
self.rel_dict[TF][gene]['pmid'].add(pmid)
else:
self.rel_dict[TF][gene] = {'method':set([method]), 'pmid':set([pmid])}
return None
def add_protein(self, protein, TF):
'''
Check if a protein exists and add it with the
required properties
'''
is_node = self.neo4j.check_protein(protein)
if is_node == False:
entry = self.information_dictio[protein]['Entry']
genes = self.information_dictio[protein]['GeneNames']
proteins = self.information_dictio[protein]['ProteinNames']
query = "CREATE (n:Protein {uniprotID:'%s', id:'%s', uniProtEntryName: '%s',\
uniprotGenesNames: %s, uniprotProteinNames: %s, specie: %s})"%\
(protein, protein, entry, genes, proteins, self.organism)
self.neo4j.session.run(query)
if TF == True:
query = "MATCH (n) WHERE n.id = '%s' SET n.TF = True"%\
(protein)
self.neo4j.session.run(query)
return None
def add_relationship(self, nodeA, nodeB, pmid, method):
'''
Check if a relationship exists and add it if necessary
fill the proper properties
'''
species = set([self.organism])
is_rel, r = self.neo4j.check_relationship(nodeA, nodeB, 'Pazar_relationship')
if is_rel == True:
for result in r:
method.update(a.encode('utf-8') for a in result['r']['method'])
pmid.update(a.encode('utf-8') for a in result['r']['pmid'])
species.update(a.encode('utf-8') for a in result['r']['species'])
query = 'MATCH (n)-[r]-(y) WHERE n.id = "%s" AND y.id ="%s" SET \
r.method = %s, r.pmid = %s, r.species = %s'%\
(nodeA, nodeB, list(method), list(pmid), list(species))
self.neo4j.session.run(query)
else:
query = "MATCH (n), (y) WHERE n.id = '%s' AND y.id = '%s'\
CREATE (n)-[r:Pazar_relationship {species:%s, pmid:%s, method:%s}]->(y)"%\
(nodeA, nodeB, list(species), list(pmid), list(method))
self.neo4j.session.run(query)
return None
def fill_database(self):
'''
Fill the Neo4j database using the information from the
dictionary constructed from the pazar data
'''
for k, v in self.rel_dict.iteritems():
self.add_protein(k, True)
for gene in v.keys():
method = self.rel_dict[k][gene]['method']
pmid = self.rel_dict[k][gene]['pmid']
self.add_protein(gene, False)
self.add_relationship(k, gene, pmid, method)
return None
if __name__ == '__main__':
start = time.time()
email = 'salcagal@alumni.uv.es'; brendapass = 'salvacasani91'
chebi = chebi_from_string()
chebi.chebi_connect()
brenda = brenda_annotation(email,brendapass)
brenda.access_protocol()
neo4j = graph_database(chebi, brenda,'Homo sapiens','neo4j','salva')
neo4j.connect()
uniprot_query = uniprot_queries('Homo sapiens', '9606')
pazar = pazar_database('Homo sapiens', neo4j, uniprot_query)
pazar.process_files()
pazar.fill_database()
end = time.time()
print 'The script took: ' + str(end - start)