shell=True)
print "Filtering folds in " + self.inPath + " down to hairpins."
FoldOps.filter_hairpins('data/tmp/' + self.inPath + '.folds',
'data/tmp/' + self.inPath + '.hairpins')
FileConversion.RNAL_to_fasta('data/tmp/' + self.inPath + '.hairpins',
'data/tmp/folds_from_' + self.inPath)
print "Removing redundant hairpins from " + self.inPath + "."
sl = SequenceList()
sl.load_fasta('data/tmp/folds_from_' + self.inPath)
sl.remove_all_redundant()
sl.export_fasta('data/tmp/' + self.inPath + 'nrhairpins')
print "Re-formatting fasta."
# Step one: turn the fasta into something that RNALfold will work with
FastaOps.remove_newlines('data/' + inPath, 'data/tmp/' + inPath + '.fixed')
# Step two: split the fasta for mutli-threaded processing
FastaOps.split_fasta('data/tmp/' + inPath + '.fixed', numThreads)
# Step three: Launch threads
threadPath = inPath
threadExt = 'fixed'
threads = []
for i in range(numThreads):
threads.append(myThread(threadPath + '.' + str(i) + '.' + threadExt))
for thread in threads:
thread.start()
for thread in threads:
thread.join()
FastaOps.merge_fasta('data/tmp/' + inPath + '.fixednrhairpins', numThreads)
call('cp data/tmp/' + inPath + '.fixednrhairpins data/' + inPath +
self.inPath = inPath
def run(self):
# Use newer local version of RNAfold
call('RNALfold -T '+str(foldTemp)+' -d2 --noLP -L '+str(hairpinLength)+' < data/tmp/'+self.inPath+' > data/tmp/'+self.inPath+'.folds', shell=True)
# Use older version of RNAfold
# call('progs/ViennaRNA-1.8.5/Progs/RNALfold -T '+str(foldTemp)+' -d2 -noLP -L '+str(hairpinLength)+' < data/tmp/'+self.inPath+' > data/tmp/'+self.inPath+'.folds', shell=True)
FoldOps.filter_hairpins('data/tmp/'+self.inPath+'.folds', 'data/tmp/'+self.inPath+'.hairpins', minMFE, basePairs)
FileConversion.RNAL_to_fasta('data/tmp/'+self.inPath+'.hairpins', 'data/tmp/folds_from_'+self.inPath)
sl = SequenceList()
sl.load_fasta('data/tmp/folds_from_'+self.inPath)
# sl.remove_all_redundant()
sl.export_fasta('data/tmp/'+self.inPath+'nrhairpins')
# Step one: turn the fasta into something that RNALfold will work with
FastaOps.remove_newlines('data/'+inPath, 'data/tmp/'+inPath+'.fixed')
FastaOps.convert_DNA_to_RNA('data/tmp/'+inPath+'.fixed', 'data/tmp/'+inPath+'.rna')
# Step two: split the fasta for mutli-threaded processing
FastaOps.split_fasta('data/tmp/'+inPath+'.rna', numThreads)
# Step three: Launch threads
threadPath = inPath
threadExt = 'rna'
threads = []
for i in range(numThreads):
threads.append(myThread(threadPath+'.'+str(i)+'.'+threadExt))
for thread in threads:
thread.start()
for thread in threads:
thread.join()
FastaOps.merge_fasta('data/tmp/'+inPath+'.rnanrhairpins', numThreads)
