def prepare_run(self, log, info):
workdir = info[Keys.WORKDIR]
iprophoutput = info['PEPCSV']
alleles = pso.fixallele(info['ALLELE_LIST'])
exe = info['NETMHCCONS']
self.df = pd.read_csv(iprophoutput,sep="\t", header=0)
uniqueSeq = self.df.drop_duplicates( subset=['search_hit'] )
pepseq = uniqueSeq['search_hit'].tolist()
self.outfiles, commands = pso.prepare_for_NetMhcCons(workdir, pepseq, alleles, exe)
return info, commands
def prepare_run(self, log, info):
workdir = info[Keys.WORKDIR]
iprophoutput = info['PEPCSV']
exe = info['NETMHCCONS']
dbpath = info['DB_PATH']
self.db = pd.read_csv(dbpath, sep=",", header=0)
self.iprophet = pd.read_csv(iprophoutput, sep="\t", header=0)
filesiprophet = list(self.iprophet['spectrum'])
filesiprophet = map(lambda w: w.split(".")[0], filesiprophet)
self.iprophet['fileid'] = filesiprophet
filesdb = list(self.db['FileName'])
filesdb = map(lambda w: os.path.splitext(w)[0], filesdb)
self.db['fileid'] = filesdb
self.mergefiles = self.iprophet.merge(self.db, left_on='fileid', right_on='fileid', how='inner')
sampleIDs = self.mergefiles['SampleID'].unique()
self.outfiles = []
self.commands = []
for sampleID in sampleIDs:
allSet = self.mergefiles[self.mergefiles['SampleID'] == sampleID]
alleles = (allSet['MHCAllele'].unique()).tolist()
if (len(alleles) != 1):
log.warning("there is more than one allele : {}".format('-'.join(alleles)))
pepseq = (allSet['search_hit'].unique()).tolist()
alleles = alleles[0].split(',')
tmpdir = os.path.join(workdir, sampleID)
if not os.path.exists(tmpdir):
os.makedirs(tmpdir)
print tmpdir
outfiles, commands = pso.prepare_for_NetMhcCons(tmpdir, pepseq, alleles, exe)
self.outfiles += outfiles
self.commands += commands
return info, self.commands
