import os.path
import gzip
import csv
from graphdb_builder import mapping as mp, builder_utils
[docs]def parser(databases_directory, importDirectory, drug_source=None, download=True, db="STRING"):
config = builder_utils.get_config(config_name="stringConfig.yml", data_type='databases')
mapping = mp.getSTRINGMapping(download=False)
stored = set()
relationship = None
cutoff = config['STRING_cutoff']
header = config['header']
drugmapping = {}
if db == "STITCH":
evidences = ["experimental", "prediction", "database", "textmining", "score"]
relationship = "COMPILED_INTERACTS_WITH"
url = config['STITCH_url']
outputfile = os.path.join(importDirectory, "stitch_associated_with.tsv")
drugmapping = mp.getSTRINGMapping(source=drug_source, download=download, db=db)
elif db == "STRING":
evidences = ["Neighborhood in the Genome", "Gene fusions", "Co-ocurrence across genomes", "Co-expression", "Experimental/biochemical data", "Association in curated databases", "Text-mining"]
relationship = "COMPILED_TARGETS"
outputfile = os.path.join(importDirectory, "string_interacts_with.tsv")
url = config['STRING_url']
directory = os.path.join(databases_directory, db)
builder_utils.checkDirectory(directory)
fileName = os.path.join(directory, url.split('/')[-1])
if download:
builder_utils.downloadDB(url, directory)
f = os.path.join(directory, fileName)
associations = gzip.open(f, 'r')
first = True
with open(outputfile, 'w') as csvfile:
writer = csv.writer(csvfile, delimiter='\t', escapechar='\\', quotechar='"', quoting=csv.QUOTE_ALL)
writer.writerow(header)
for line in associations:
if first:
first = False
continue
data = line.decode('utf-8').rstrip("\r\n").split()
intA = data[0]
intB = data[1]
scores = data[2:]
fscores = [str(float(score)/1000) for score in scores]
if db == "STRING":
if intA in mapping and intB in mapping and float(fscores[-1]) >= cutoff:
for aliasA in mapping[intA]:
for aliasB in mapping[intB]:
if (aliasA, aliasB) not in stored:
row = (aliasA, aliasB, relationship, "association", db, ",".join(evidences), ",".join(fscores[0:-1]), fscores[-1])
stored.add((aliasA, aliasB))
stored.add((aliasB, aliasB))
writer.writerow(row)
elif db == "STITCH":
if intA in drugmapping and intB in mapping and float(fscores[-1]) >= cutoff:
for aliasA in drugmapping[intA]:
for aliasB in mapping[intB]:
if (aliasA, aliasB) not in stored:
row = (aliasA, aliasB, relationship, "association", db, ",".join(evidences), ",".join(fscores[0:-1]), fscores[-1])
stored.add((aliasA, aliasB))
stored.add((aliasB, aliasB))
writer.writerow(row)
associations.close()
return mapping, drugmapping
[docs]def parseActions(databases_directory, importDirectory, proteinMapping, drugMapping=None, download=True, db="STRING"):
config = builder_utils.get_config(config_name="stringConfig.yml", data_type='databases')
url = None
bool_dict = {'t': True, 'T': True, 'True': True, 'TRUE': True, 'f': False, 'F': False, 'False': False, 'FALSE': False}
header = config['header_actions']
relationship = "COMPILED_ACTS_ON"
stored = set()
if db == "STRING":
url = config['STRING_actions_url']
outputfile = os.path.join(importDirectory, "string_protein_acts_on_protein.tsv")
elif db == "STITCH":
url = config['STITCH_actions_url']
outputfile = os.path.join(importDirectory, "stitch_drug_acts_on_protein.tsv")
directory = os.path.join(databases_directory, db)
builder_utils.checkDirectory(directory)
fileName = os.path.join(directory, url.split('/')[-1])
if download:
builder_utils.downloadDB(url, directory)
f = os.path.join(directory, fileName)
associations = gzip.open(f, 'r')
first = True
with open(outputfile, 'w') as csvfile:
writer = csv.writer(csvfile, delimiter='\t', escapechar='\\', quotechar='"', quoting=csv.QUOTE_ALL)
writer.writerow(header)
for line in associations:
if first:
first = False
continue
data = line.decode('utf-8').rstrip("\r\n").split()
intA = data[0]
intB = data[1]
action = data[2]
score = float(data[-1])/1000
directionality = bool_dict[data[-3]] if db == "STRING" else True
if intB in proteinMapping:
aliasesA = []
if intA in drugMapping:
aliasesA = drugMapping[intA]
elif intA in proteinMapping:
aliasesA = proteinMapping[intA]
for aliasA in aliasesA:
for aliasB in proteinMapping[intB]:
if (aliasA, aliasB, action) not in stored:
row = (aliasA, aliasB, relationship, action, directionality, score, db)
writer.writerow(row)
stored.add((aliasA, aliasB, action))
stored.add((aliasB, aliasA, action))
associations.close()