def main(args):
#Get R ready
# Get current pathway
myPath = os.path.abspath(os.path.dirname(os.path.realpath(__file__)))
# Stablish path for LASSO script
my_r_script_path = os.path.join(myPath, "lasso_enet.R")
logger.info(my_r_script_path)
# Activate pandas2ri
pandas2ri.activate()
# Running LASSO R sctrip
with open(my_r_script_path, 'r') as f:
rFile = f.read()
lassoEnetScript = STAP(rFile, "lasso_enet")
# Importing data trought interface
dat = wideToDesign(args.input,
args.design,
args.uniqID,
group=args.group,
logger=logger)
# Cleaning from missing data
dat.dropMissing()
# Transpossing data
dat.trans = dat.transpose()
dat.trans.columns.name = ""
# Dropping nan columns from design
removed = dat.design[dat.design[dat.group] == "nan"]
dat.design = dat.design[dat.design[dat.group] != "nan"]
dat.trans.drop(removed.index.values, axis=0, inplace=True)
logger.info("{0} removed from analysis".format(removed.index.values))
dat.design.rename(columns={dat.group: "group"}, inplace=True)
dat.trans.rename(columns={dat.group: "group"}, inplace=True)
#Generate a group List
groupList = [
title for title, group in dat.design.groupby("group")
if len(group.index) > 2
]
#Turn group list into pairwise combinations
comboMatrix = np.array(list(it.combinations(groupList, 2)))
comboLength = len(comboMatrix)
#Run R
correct_list_of_names = np.array(dat.trans.columns.values.tolist())
returns = lassoEnetScript.lassoEN(dat.trans, dat.design, args.uniqID,
correct_list_of_names, comboMatrix,
comboLength, args.alpha, args.plots)
robjects.r['write.table'](returns[0],
file=args.coefficients,
sep='\t',
quote=False,
row_names=False,
col_names=True)
robjects.r['write.table'](returns[1],
file=args.flags,
sep='\t',
quote=False,
row_names=False,
col_names=True)
# Finishing
logger.info("Script Complete!")
