def __call__(self, seqs, all_seqs):
"""call the runner like a function"""
with tempfile.NamedTemporaryFile(prefix='weeder.fasta',
delete=False) as outfile:
filename = outfile.name
logging.info("Run Weeder on FASTA file: '%s'", filename)
st.write_sequences_to_fasta_file(outfile, seqs.items())
pssms = weeder.run_weeder(filename)
meme_outfile = '%s.meme' % filename
dbfile = self.meme_suite.make_sequence_file(
[(feature_id, locseq[1])
for feature_id, locseq in all_seqs.items()])
logging.info("# PSSMS created: %d", len(pssms))
logging.info("run MAST on '%s'", meme_outfile)
motif_infos = []
for i in xrange(len(pssms)):
pssm = pssms[i]
motif_infos.append(meme.MemeMotifInfo(pssm.values(), i + 1,
pssm.sequence_length(),
len(pssm.sites()),
None, pssm.evalue(),
pssm.sites()))
try:
mast_out = self.meme_suite.mast(
meme_outfile, dbfile,
self.meme_suite.global_background_file())
pe_values, annotations = meme.read_mast_output(mast_out,
seqs.keys())
return meme.MemeRunResult(pe_values, annotations, motif_infos)
except:
return meme.MemeRunResult([], {}, [])
def test_write_sequences_to_fasta_file(self):
"""Tests writing to a FASTA file"""
seqs = st.read_sequences_from_fasta_file('testdata/fasta_test.fa')
with open('/tmp/fasta_tmp.fa', 'w') as outputfile:
st.write_sequences_to_fasta_file(outputfile, seqs)
seqs2 = st.read_sequences_from_fasta_file('/tmp/fasta_tmp.fa')
self.assertEquals(seqs, seqs2)
def test_write_sequences_to_fasta_file(self):
"""Tests writing to a FASTA file"""
seqs = st.read_sequences_from_fasta_file('testdata/fasta_test.fa')
with open('/tmp/fasta_tmp.fa', 'w') as outputfile:
st.write_sequences_to_fasta_file(outputfile, seqs)
seqs2 = st.read_sequences_from_fasta_file('/tmp/fasta_tmp.fa')
self.assertEquals(seqs, seqs2)
def make_sequence_file(self, seqs):
"""Creates a FASTA file from a list of(feature_id, sequence)
pairs"""
filename = None
with tempfile.NamedTemporaryFile(prefix='memeseqs',
delete=False) as outfile:
filename = outfile.name
st.write_sequences_to_fasta_file(outfile, seqs)
return filename
def make_sequence_file(self, seqs):
"""Creates a FASTA file from a list of(feature_id, sequence)
pairs"""
filename = None
with tempfile.NamedTemporaryFile(prefix='memeseqs',
delete=False) as outfile:
filename = outfile.name
st.write_sequences_to_fasta_file(outfile, seqs)
return filename
def __call__(self, params):
"""call the runner like a function"""
with tempfile.NamedTemporaryFile(prefix='weeder.fasta',
delete=False) as outfile:
filename = outfile.name
logging.debug("Run Weeder on FASTA file: '%s'", filename)
st.write_sequences_to_fasta_file(outfile, params.seqs.iteritems())
try:
dbfile = None
meme_outfile, pssms = weeder.run_weeder(filename, params, self.config_params,
self.meme_suite.bgmodel)
if len(pssms) == 0:
logging.debug('no PSSMS generated, skipping cluster')
return meme.MemeRunResult([], {}, [])
dbfile = self.meme_suite.make_sequence_file(
[(feature_id, locseq[1])
for feature_id, locseq in params.used_seqs.iteritems()])
logging.debug("# PSSMS created: %d %s", len(pssms), str([i.consensus_motif() for i in pssms]))
logging.debug("run MAST on '%s', dbfile: '%s'", meme_outfile, dbfile)
motif_infos = []
for i in xrange(len(pssms)):
pssm = pssms[i]
motif_infos.append(meme.MemeMotifInfo(pssm.values, i + 1,
pssm.sequence_length(),
len(pssm.sites),
None, pssm.e_value,
pssm.sites))
mast_out = self.meme_suite.mast(meme_outfile, dbfile,
self.meme_suite.global_background_file())
if 'keep_mastout' in self.config_params['debug']:
with open('%s.mast' % meme_outfile, 'w') as outfile:
outfile.write(mast_out)
pe_values, annotations = self.meme_suite.read_mast_output(mast_out,
params.seqs.keys())
return meme.MemeRunResult(pe_values, annotations, motif_infos)
except:
e = sys.exc_info()[0]
print e
raise
return meme.MemeRunResult([], {}, [])
finally:
if self.__remove_tempfiles:
for fileExtension in ['', '.wee', '.mix', '.html', '.meme', '.1.f1', '.1.f2', '.2.f1', '.2.f2']:
tmpName = filename + fileExtension
if os.path.exists(tmpName):
try:
os.remove(tmpName)
except:
logging.warn("could not remove tmp file:'%s'", tmpName)
try:
if dbfile:
os.remove(dbfile)
except:
logging.warn("could not remove tmp file:'%s'", dbfile)
def test_write_sequences_to_fasta_file_empty_seqs(self):
"""Tests ensures that only non-empty sequences will be written to FASTA"""
seqs = [['seq1', 'TATATA'], ['seq2', '']]
with open('/tmp/fasta_tmp.fa', 'w') as outputfile:
st.write_sequences_to_fasta_file(outputfile, seqs)
seqs2 = st.read_sequences_from_fasta_file('/tmp/fasta_tmp.fa')
self.assertEquals(1, len(seqs2))
self.assertEquals(seqs[0][0], seqs2[0][0])
self.assertEquals(seqs[0][1], seqs2[0][1])
def test_write_sequences_to_fasta_file_empty_seqs(self):
"""Tests ensures that only non-empty sequences will be written to FASTA"""
seqs = [['seq1', 'TATATA'], ['seq2', '']]
with open('/tmp/fasta_tmp.fa', 'w') as outputfile:
st.write_sequences_to_fasta_file(outputfile, seqs)
seqs2 = st.read_sequences_from_fasta_file('/tmp/fasta_tmp.fa')
self.assertEquals(1, len(seqs2))
self.assertEquals(seqs[0][0], seqs2[0][0])
self.assertEquals(seqs[0][1], seqs2[0][1])
def __call__(self, params):
"""call the runner like a function"""
with tempfile.NamedTemporaryFile(prefix='weeder.fasta',
delete=False) as outfile:
filename = outfile.name
logging.info("Run Weeder on FASTA file: '%s'", filename)
st.write_sequences_to_fasta_file(outfile, params.seqs.items())
pssms = weeder.run_weeder(filename)
meme_outfile = '%s.meme' % filename
dbfile = self.meme_suite.make_sequence_file([
(feature_id, locseq[1])
for feature_id, locseq in params.used_seqs.items()
])
logging.info("# PSSMS created: %d %s", len(pssms),
str([i.consensus_motif() for i in pssms]))
logging.info("run MAST on '%s'", meme_outfile)
motif_infos = []
for i in xrange(len(pssms)):
pssm = pssms[i]
motif_infos.append(
meme.MemeMotifInfo(pssm.values, i + 1, pssm.sequence_length(),
len(pssm.sites), None, pssm.e_value,
pssm.sites))
try:
mast_out = self.meme_suite.mast(
meme_outfile, dbfile, self.meme_suite.global_background_file())
pe_values, annotations = meme.read_mast_output(
mast_out, params.seqs.keys())
return meme.MemeRunResult(pe_values, annotations, motif_infos)
except:
return meme.MemeRunResult([], {}, [])
finally:
if self.__remove_tempfiles:
for fileExtension in [
'', '.wee', '.mix', '.html', '.meme', '.1.f1', '.1.f2',
'.2.f1', '.2.f2'
]:
tmpName = filename + fileExtension
if os.path.exists(tmpName):
try:
os.remove(tmpName)
except:
logging.warn("could not remove tmp file:'%s'",
tmpName)
try:
os.remove(dbfile)
except:
logging.warn("could not remove tmp file:'%s'", dbfile)
def __call__(self, params):
"""call the runner like a function"""
with tempfile.NamedTemporaryFile(prefix='weeder.fasta',
delete=False) as outfile:
filename = outfile.name
logging.info("Run Weeder on FASTA file: '%s'", filename)
st.write_sequences_to_fasta_file(outfile, params.seqs.items())
if seqtype=='upstream':
freqfile = 'HS'
elif seqtype=='p3utr':
freqfile = 'HS3P'
pssms = weeder.run_weeder(filename, freqfile)
meme_outfile = '%s.meme' % filename
dbfile = self.meme_suite.make_sequence_file(
[(feature_id, locseq[1])
for feature_id, locseq in params.used_seqs.items()])
logging.info("# PSSMS created: %d %s", len(pssms),str([i.consensus_motif() for i in pssms]))
logging.info("run MAST on '%s'", meme_outfile)
motif_infos = []
for i in xrange(len(pssms)):
pssm = pssms[i]
motif_infos.append(meme.MemeMotifInfo(pssm.values, i + 1,
pssm.sequence_length(),
len(pssm.sites),
None, pssm.e_value,
pssm.sites))
try:
mast_out = self.meme_suite.mast(
meme_outfile, dbfile,
self.meme_suite.global_background_file())
pe_values, annotations = meme.read_mast_output(mast_out,
params.seqs.keys())
return meme.MemeRunResult(pe_values, annotations, motif_infos)
except:
return meme.MemeRunResult([], {}, [])
finally:
if self.__remove_tempfiles:
for fileExtension in ['','.wee','.mix','.html','.meme','.1.f1','.1.f2','.2.f1','.2.f2']:
tmpName = filename+fileExtension
if os.path.exists(tmpName):
try:
os.remove(tmpName)
except:
logging.warn("could not remove tmp file:'%s'", tmpName)
try:
os.remove(dbfile)
except:
logging.warn("could not remove tmp file:'%s'", dbfile)
def make_sequences( genome_fasta_file, gene_features_file,
outfile='sequences.csv', distance={'upstream':300,'downstream':100}, from_end=False, fasta=False ):
if from_end:
distance = ( distance['upstream'], distance['downstream'] )
else:
'''WARNING: as of 2012-03-22, the st.extract functions used flipped distances!
e.g. distance[1] is the UPSTREAM distance and distance[0] is the DOWNSTREAM
CHECK YOUR SEQUENCES after running this! Also, a negative number is expected for
DOWNSTREAM. So, (-100,300) must be passed to st.extract_upstream in order to get
a sequence from 300 upstream to 100 downstream. WEIRD!'''
distance = (-1*distance['downstream'],distance['upstream'])
contig_sequences = st.read_sequences_from_fasta_file( genome_fasta_file )
# convert contig_sequences to dictionary (this func returns a list of tuples)
contig_dict = {}
for name, seq in contig_sequences:
contig_dict[name] = seq
print 'loaded %i contigs' %len(contig_dict)
print string.join( [ '%s: %ibp' %(a,len(b)) for a,b in contig_dict.items()] , ',' )
features = st.read_features_from_file( gene_features_file )
print 'loaded %i features' %len(features)
# print str(features.values()[1])
sequences = []
for feature in features.values():
location = feature.location()
# print location, location.contig, distance, feature.id()
if from_end:
sequences.append( ( feature.id(), st.extract_downstream(contig_dict[location.contig], location, distance)[1] ) )
else:
sequences.append( ( feature.id(), st.extract_upstream(contig_dict[location.contig], location, distance)[1] ) )
# print sequences[feature.id()]
outf = open(outfile,'w')
if fasta: st.write_sequences_to_fasta_file(outf,sequences)
else:
sep = ','
for id, seq in sequences:
outf.write( '%s%s%s\n' %(id,sep,seq) )
outf.close()
def make_sequences( genome_fasta_file, gene_features_file,
outfile='sequences.csv', distance={'upstream':300,'downstream':100}, from_end=False, fasta=False ):
if from_end:
distance = ( distance['upstream'], distance['downstream'] )
else:
'''WARNING: as of 2012-03-22, the st.extract functions used flipped distances!
e.g. distance[1] is the UPSTREAM distance and distance[0] is the DOWNSTREAM
CHECK YOUR SEQUENCES after running this! Also, a negative number is expected for
DOWNSTREAM. So, (-100,300) must be passed to st.extract_upstream in order to get
a sequence from 300 upstream to 100 downstream. WEIRD!'''
distance = (-1*distance['downstream'],distance['upstream'])
contig_sequences = st.read_sequences_from_fasta_file( genome_fasta_file )
# convert contig_sequences to dictionary (this func returns a list of tuples)
contig_dict = {}
for name, seq in contig_sequences:
contig_dict[name] = seq
print 'loaded %i contigs' %len(contig_dict)
print string.join( [ '%s: %ibp' %(a,len(b)) for a,b in contig_dict.items()] , ',' )
features = st.read_features_from_file( gene_features_file )
print 'loaded %i features' %len(features)
# print str(features.values()[1])
sequences = []
for feature in features.values():
location = feature.location
# print location, location.contig, distance, feature.id
if from_end:
sequences.append( ( feature.id, st.extract_downstream(contig_dict[location.contig], location, distance)[1] ) )
else:
sequences.append( ( feature.id, st.extract_upstream(contig_dict[location.contig], location, distance)[1] ) )
# print sequences[feature.id]
outf = open(outfile,'w')
if fasta: st.write_sequences_to_fasta_file(outf,sequences)
else:
sep = ','
for id, seq in sequences:
outf.write( '%s%s%s\n' %(id,sep,seq) )
outf.close()