def go(self):
"""Execution function: coordinates options used and background GC calculation, then runs
TAMO.MD.AlignAce.MetaAce and catches the output in self.output for access from MDAP.
Output is TAMO.AligAce result object."""
import time
# Calc GC background of genomic sequences representing the
# entire data set if requested.
if self.mdapOptions['background'] == 1:
self.dataStats = seqStats.calcStats(self.mdapArgs[0])
self.gcback = self.dataStats['percentGC']
# write a temp fasta file of coregulated seqs to use as input to Meme(file=TempFasta)
ctimeStr = time.ctime().replace(' ','_')
fileName = 'tempFastaOfCoRegSeqs.MDAP.%s.fas' %(ctimeStr)
tFasta = open(fileName, 'w')
tFastaTxt = Fasta.text(self.coRegSeqs[0])
tFasta.write(tFastaTxt)
# call TAMO to do its thing
self.output = MetaAce(fileName, self.width, self.iterations, self.gcback)
pass
import sys
import pickle
assert 4 >= len(sys.argv[1:]) >= 3, 'usage: python %s fastaDir iterations runName [globPatern]' \
% (sys.argv[0].split('/')[-1])
if len(sys.argv[1:]) > 3:
globPattern = sys.argv[4]
else:
globPattern = '*.fas'
fastaPaths = glob.glob(sys.argv[1]+globPattern)
gcBacks = []
for path in fastaPaths:
stats = calcStats(path)
gcBacks.append(stats['percentGC'])
metaAceObjs = []
for i in range(len(fastaPaths)):
metaAceObjs.append(MetaAce(fastaPaths[i],iterations=int(sys.argv[2]),gcback=gcBacks[i]))
outFile = open('%s%s.pickle' % (sys.argv[1],sys.argv[3]),'w')
pickle.dump(tuple(metaAceObjs),outFile)