import os
import pandas as pd
from pathlib import Path
import numpy as np
[docs]def run(RunnerObj):
'''
Function to run GENIE3 algorithm
:param RunnerObj: An instance of the :class:`BLRun`
'''
inputPath = "data" + str(RunnerObj.inputDir).split(str(Path.cwd()))[1] + \
"/GENIE3/ExpressionData.csv"
# make output dirs if they do not exist:
outDir = "outputs/"+str(RunnerObj.inputDir).split("inputs/")[1]+"/GENIE3/"
os.makedirs(outDir, exist_ok = True)
outPath = "data/" + str(outDir) + 'outFile.txt'
cmdToRun = ' '.join(['docker run --rm -v', str(Path.cwd())+':/data/ --expose=41269',
'arboreto:base /bin/sh -c \"time -v -o', "data/" + str(outDir) + 'time.txt', 'python runArboreto.py --algo=GENIE3',
'--inFile='+inputPath, '--outFile='+outPath, '\"'])
print(cmdToRun)
os.system(cmdToRun)
[docs]def parseOutput(RunnerObj):
'''
Function to parse outputs from GENIE3.
:param RunnerObj: An instance of the :class:`BLRun`
'''
# Quit if output directory does not exist
outDir = "outputs/"+str(RunnerObj.inputDir).split("inputs/")[1]+"/GENIE3/"
# Read output
OutDF = pd.read_csv(outDir+'outFile.txt', sep = '\t', header = 0)
if not Path(outDir+'outFile.txt').exists():
print(outDir+'outFile.txt'+'does not exist, skipping...')
return
outFile = open(outDir + 'rankedEdges.csv','w')
outFile.write('Gene1'+'\t'+'Gene2'+'\t'+'EdgeWeight'+'\n')
for idx, row in OutDF.iterrows():
outFile.write('\t'.join([row['TF'],row['target'],str(row['importance'])])+'\n')
outFile.close()