def test_cdhit_clusters_from_seqs(self):
"""cdhit_clusters_from_seqs returns expected clusters"""
exp = [['cdhit_test_seqs_0'],['cdhit_test_seqs_1'],\
['cdhit_test_seqs_2'],['cdhit_test_seqs_3'],\
['cdhit_test_seqs_4'],['cdhit_test_seqs_5'],\
['cdhit_test_seqs_6','cdhit_test_seqs_8'],\
['cdhit_test_seqs_7'],['cdhit_test_seqs_9']]
obs = cdhit_clusters_from_seqs(dna_seqs, DNA)
self.assertEqual(obs, exp)
def test_cdhit_clusters_from_seqs(self):
"""cdhit_clusters_from_seqs returns expected clusters"""
exp = [['cdhit_test_seqs_0'],['cdhit_test_seqs_1'],\
['cdhit_test_seqs_2'],['cdhit_test_seqs_3'],\
['cdhit_test_seqs_4'],['cdhit_test_seqs_5'],\
['cdhit_test_seqs_6','cdhit_test_seqs_8'],\
['cdhit_test_seqs_7'],['cdhit_test_seqs_9']]
obs = cdhit_clusters_from_seqs(dna_seqs, DNA)
self.assertEqual(obs, exp)
def __call__(self,
seq_path,
result_path=None,
log_path=None,
id_len=0,
prefix_prefilter_length=None,
trie_prefilter=False):
"""Returns dict mapping {otu_id:[seq_ids]} for each otu.
Parameters:
seq_path: path to file of sequences
result_path: path to file of results. If specified,
dumps the result to the desired path instead of returning it.
log_path: path to log, which includes dump of params.
id_len: if set, truncates ids to n chars (you don't want this!)
prefix_prefilter_length: prefilters the sequence collection so
sequences whose first prefix_prefilter_length characters are
identical will automatically be grouped into the same OTU [off by
default, 100 is typically a good value if this filtering is
desired] -- useful for large sequence collections, when cdhit doesn't
scale well
trie_prefilter: prefilter the sequence collection such that all sequences
which are a prefix of another sequence are clustered with the other sequence.
Togther with cd-hit this is a non-heuristic filter reduces run time a lot.
Still a bit slower than the prefix_prefilter toggled with prefix_prefilter_length.
"""
moltype = DNA
log_lines = []
# create the params dict to pass to cd-hit-est -- IS THERE A
# BETTER WAY TO MAKE self.Params INTO THE params DICT TO PASS
# TO THE APPLICATION CONTROLLERS?
cd_hit_params = copy(self.Params)
del cd_hit_params['Application']
del cd_hit_params['Algorithm']
cd_hit_params['-d'] = id_len #turn off id truncation
cd_hit_params['-g'] = "1"
if (prefix_prefilter_length != None and trie_prefilter):
log_lines.append("Both prefilters selected. Deactivate \
trie_prefilter")
trie_prefilter = False
if prefix_prefilter_length != None:
log_lines.append(\
'Prefix-based prefiltering, prefix length: %d' \
% prefix_prefilter_length )
seqs, filter_map = self._prefilter_exact_prefixes(\
MinimalFastaParser(open(seq_path)),prefix_prefilter_length)
log_lines.append(\
'Prefix-based prefiltering, post-filter num seqs: %d' \
% len(seqs))
elif trie_prefilter:
log_lines.append(\
'Trie-based prefiltering')
seqs, filter_map = self._prefilter_with_trie(seq_path)
log_lines.append(\
'Trie-based prefiltering, post-filter num seqs: %d' \
% len(seqs))
else:
log_lines.append('No prefix-based prefiltering.')
# Load the seq path. Right now, cdhit_clusters_from_seqs
# doesn't support being passed a file path even though the
# seqs do get written to a fasta file before being passed
# to cd-hit-est. We may want to change that in the future
# to avoid the overhead of loading large sequence collections
# during this step.
seqs = LoadSeqs(seq_path,
moltype=moltype,
aligned=False,
label_to_name=lambda x: x.split()[0])
# Get the clusters by running cd-hit-est against the
# sequence collection
clusters = cdhit_clusters_from_seqs(\
seqs=seqs,moltype=moltype,params=cd_hit_params)
if prefix_prefilter_length != None or trie_prefilter:
clusters = self._map_filtered_clusters_to_full_clusters(\
clusters,filter_map)
if result_path:
# if the user provided a result_path, write the
# results to file with one tab-separated line per
# cluster
of = open(result_path, 'w')
for i, cluster in enumerate(clusters):
of.write('%s\t%s\n' % (i, '\t'.join(cluster)))
of.close()
result = None
log_lines.append('Result path: %s' % result_path)
else:
# if the user did not provide a result_path, store
# the clusters in a dict of {otu_id:[seq_ids]}, where
# otu_id is arbitrary
result = dict(enumerate(clusters))
log_lines.append('Result path: None, returned as dict.')
if log_path:
# if the user provided a log file path, log the run
log_file = open(log_path, 'w')
log_lines = [str(self)] + log_lines
log_file.write('\n'.join(log_lines))
# return the result (note this is None if the data was
# written to file)
return result
def __call__(
self, seq_path, result_path=None, log_path=None, id_len=0, prefix_prefilter_length=None, trie_prefilter=False
):
"""Returns dict mapping {otu_id:[seq_ids]} for each otu.
Parameters:
seq_path: path to file of sequences
result_path: path to file of results. If specified,
dumps the result to the desired path instead of returning it.
log_path: path to log, which includes dump of params.
id_len: if set, truncates ids to n chars (you don't want this!)
prefix_prefilter_length: prefilters the sequence collection so
sequences whose first prefix_prefilter_length characters are
identical will automatically be grouped into the same OTU [off by
default, 100 is typically a good value if this filtering is
desired] -- useful for large sequence collections, when cdhit doesn't
scale well
trie_prefilter: prefilter the sequence collection such that all sequences
which are a prefix of another sequence are clustered with the other sequence.
Togther with cd-hit this is a non-heuristic filter reduces run time a lot.
Still a bit slower than the prefix_prefilter toggled with prefix_prefilter_length.
"""
moltype = DNA
log_lines = []
# create the params dict to pass to cd-hit-est -- IS THERE A
# BETTER WAY TO MAKE self.Params INTO THE params DICT TO PASS
# TO THE APPLICATION CONTROLLERS?
cd_hit_params = copy(self.Params)
del cd_hit_params["Application"]
del cd_hit_params["Algorithm"]
cd_hit_params["-d"] = id_len # turn off id truncation
cd_hit_params["-g"] = "1"
if prefix_prefilter_length != None and trie_prefilter:
log_lines.append(
"Both prefilters selected. Deactivate \
trie_prefilter"
)
trie_prefilter = False
if prefix_prefilter_length != None:
log_lines.append("Prefix-based prefiltering, prefix length: %d" % prefix_prefilter_length)
seqs, filter_map = self._prefilter_exact_prefixes(
MinimalFastaParser(open(seq_path)), prefix_prefilter_length
)
log_lines.append("Prefix-based prefiltering, post-filter num seqs: %d" % len(seqs))
elif trie_prefilter:
log_lines.append("Trie-based prefiltering")
seqs, filter_map = self._prefilter_with_trie(seq_path)
log_lines.append("Trie-based prefiltering, post-filter num seqs: %d" % len(seqs))
else:
log_lines.append("No prefix-based prefiltering.")
# Load the seq path. Right now, cdhit_clusters_from_seqs
# doesn't support being passed a file path even though the
# seqs do get written to a fasta file before being passed
# to cd-hit-est. We may want to change that in the future
# to avoid the overhead of loading large sequence collections
# during this step.
seqs = LoadSeqs(seq_path, moltype=moltype, aligned=False, label_to_name=lambda x: x.split()[0])
# Get the clusters by running cd-hit-est against the
# sequence collection
clusters = cdhit_clusters_from_seqs(seqs=seqs, moltype=moltype, params=cd_hit_params)
if prefix_prefilter_length != None or trie_prefilter:
clusters = self._map_filtered_clusters_to_full_clusters(clusters, filter_map)
if result_path:
# if the user provided a result_path, write the
# results to file with one tab-separated line per
# cluster
of = open(result_path, "w")
for i, cluster in enumerate(clusters):
of.write("%s\t%s\n" % (i, "\t".join(cluster)))
of.close()
result = None
log_lines.append("Result path: %s" % result_path)
else:
# if the user did not provide a result_path, store
# the clusters in a dict of {otu_id:[seq_ids]}, where
# otu_id is arbitrary
result = dict(enumerate(clusters))
log_lines.append("Result path: None, returned as dict.")
if log_path:
# if the user provided a log file path, log the run
log_file = open(log_path, "w")
log_lines = [str(self)] + log_lines
log_file.write("\n".join(log_lines))
# return the result (note this is None if the data was
# written to file)
return result
