def test_split_fasta_diff_num_seqs_per_file_alt(self):
"""split_fasta funcs always catches all seqs
"""
# start with 59 seqs (b/c it's prime, so should make more
# confusing splits)
in_seqs = SequenceCollection.from_fasta_records(
[('seq%s' % k, 'AACCTTAA') for k in range(59)], DNA)
infile = in_seqs.to_fasta().split('\n')
# test seqs_per_file from 1 to 1000
for i in range(1, 1000):
fd, filename_prefix = mkstemp(dir=get_qiime_temp_dir(),
prefix='split_fasta_tests',
suffix='')
close(fd)
actual = split_fasta(infile, i, filename_prefix)
actual_seqs = []
for fp in actual:
actual_seqs += list(open(fp))
# remove the files now, so if the test fails they still get
# cleaned up
remove_files(actual)
# building seq collections from infile and the split files result in
# equivalent seq collections
self.assertEqual(
SequenceCollection.from_fasta_records(parse_fasta(infile), DNA),
SequenceCollection.from_fasta_records(parse_fasta(actual_seqs), DNA))
def test_init(self):
"""Initialization functions as expected with varied input types
"""
SequenceCollection(self.seqs1)
SequenceCollection(self.seqs2)
SequenceCollection(self.seqs3)
SequenceCollection([])
def test_split_fasta_diff_num_seqs_per_file(self):
"""split_fasta funcs as expected when diff num seqs go to each file
"""
fd, filename_prefix = mkstemp(dir=get_qiime_temp_dir(),
prefix='split_fasta_tests',
suffix='')
close(fd)
infile = ['>seq1', 'AACCTTAA', '>seq2', 'TTAACC', 'AATTAA',
'>seq3', 'CCTT--AA']
actual = split_fasta(infile, 2, filename_prefix)
actual_seqs = []
for fp in actual:
actual_seqs += list(open(fp))
remove_files(actual)
expected = ['%s.%d.fasta' % (filename_prefix, i) for i in range(2)]
# list of file paths is as expected
self.assertEqual(actual, expected)
# building seq collections from infile and the split files result in
# equivalent seq collections
self.assertEqual(
SequenceCollection.from_fasta_records(parse_fasta(infile), DNA),
SequenceCollection.from_fasta_records(parse_fasta(actual_seqs), DNA))
def __call__(self,
seq_path,
result_path=None,
log_path=None,
failure_path=None):
# load candidate sequences
seq_file = open(seq_path, 'U')
candidate_sequences = parse_fasta(seq_file)
# load template sequences
template_alignment = []
template_alignment_fp = self.Params['template_filepath']
for seq_id, seq in parse_fasta(open(template_alignment_fp)):
# replace '.' characters with '-' characters
template_alignment.append((seq_id, seq.replace('.', '-').upper()))
template_alignment = Alignment.from_fasta_records(template_alignment,
DNASequence,
validate=True)
# initialize_logger
logger = NastLogger(log_path)
# get function for pairwise alignment method
pairwise_alignment_f = pairwise_alignment_methods[
self.Params['pairwise_alignment_method']]
pynast_aligned, pynast_failed = pynast_seqs(
candidate_sequences,
template_alignment,
min_pct=self.Params['min_pct'],
min_len=self.Params['min_len'],
align_unaligned_seqs_f=pairwise_alignment_f,
logger=logger,
temp_dir=get_qiime_temp_dir())
logger.record(str(self))
for i, seq in enumerate(pynast_failed):
skb_seq = DNASequence(str(seq), id=seq.Name)
pynast_failed[i] = skb_seq
pynast_failed = SequenceCollection(pynast_failed)
for i, seq in enumerate(pynast_aligned):
skb_seq = DNASequence(str(seq), id=seq.Name)
pynast_aligned[i] = skb_seq
pynast_aligned = Alignment(pynast_aligned)
if failure_path is not None:
fail_file = open(failure_path, 'w')
fail_file.write(pynast_failed.to_fasta())
fail_file.close()
if result_path is not None:
result_file = open(result_path, 'w')
result_file.write(pynast_aligned.to_fasta())
result_file.close()
return None
else:
return pynast_aligned
def test_init_validate(self):
"""initialization with validation functions as expected
"""
SequenceCollection(self.seqs1, validate=True)
SequenceCollection(self.seqs1, validate=True)
# can't validate self.seqs2 as a DNASequence
self.assertRaises(SequenceCollectionError,
SequenceCollection,
self.invalid_s1,
validate=True)
def __call__(self, seq_path, result_path=None, log_path=None,
failure_path=None):
# load candidate sequences
seq_file = open(seq_path, 'U')
candidate_sequences = parse_fasta(seq_file)
# load template sequences
template_alignment = []
template_alignment_fp = self.Params['template_filepath']
for seq_id, seq in parse_fasta(open(template_alignment_fp)):
# replace '.' characters with '-' characters
template_alignment.append((seq_id, seq.replace('.', '-').upper()))
template_alignment = Alignment.from_fasta_records(
template_alignment, DNASequence, validate=True)
# initialize_logger
logger = NastLogger(log_path)
# get function for pairwise alignment method
pairwise_alignment_f = pairwise_alignment_methods[
self.Params['pairwise_alignment_method']]
pynast_aligned, pynast_failed = pynast_seqs(
candidate_sequences,
template_alignment,
min_pct=self.Params['min_pct'],
min_len=self.Params['min_len'],
align_unaligned_seqs_f=pairwise_alignment_f,
logger=logger,
temp_dir=get_qiime_temp_dir())
logger.record(str(self))
for i, seq in enumerate(pynast_failed):
skb_seq = DNASequence(str(seq), identifier=seq.Name)
pynast_failed[i] = skb_seq
pynast_failed = SequenceCollection(pynast_failed)
for i, seq in enumerate(pynast_aligned):
skb_seq = DNASequence(str(seq), identifier=seq.Name)
pynast_aligned[i] = skb_seq
pynast_aligned = Alignment(pynast_aligned)
if failure_path is not None:
fail_file = open(failure_path, 'w')
fail_file.write(pynast_failed.to_fasta())
fail_file.close()
if result_path is not None:
result_file = open(result_path, 'w')
result_file.write(pynast_aligned.to_fasta())
result_file.close()
return None
else:
return pynast_aligned
def filter_samples(prefs, data, dir_path='', filename=None):
"""processes the filtering of the otus file and representative seq set, then
writes filtered otus and filtered representative seq set files"""
aln = data['aln']
otus = data['otus']
# filter the otus file based on which samples to remove
new_otus_list = filter_otus(otus, prefs)
filtered_otus_output_filepath = '%s/%s_sfiltered_otus.txt' \
% (dir_path, filename)
filtered_otus_output_filepath = open(filtered_otus_output_filepath, 'w')
# Write out a new otus file
for key in (new_otus_list):
filtered_otus_output_filepath.write(key[0])
for j in key[1]:
filtered_otus_output_filepath.write('\t' + str(j))
filtered_otus_output_filepath.write('\n')
filtered_otus_output_filepath.close()
# filter seq set
filtered_seqs, removed_seqs = filter_aln_by_otus(aln, prefs)
# write a fasta containing list of sequences removed from
# representative set
if len(removed_seqs) > 0:
removed_seqs = SequenceCollection.from_fasta_records(
[(e[0], str(e[1])) for e in removed_seqs], DNA)
else:
raise ValueError(
'No sequences were removed. Did you specify the correct Sample ID?'
)
output_filepath2 = '%s/%s_sremoved.fasta' % (dir_path, filename)
output_file2 = open(output_filepath2, 'w')
output_file2.write(removed_seqs.to_fasta())
output_file2.close()
# write a fasta containing the filtered representative seqs
if len(filtered_seqs) > 0:
filtered_seqs = SequenceCollection.from_fasta_records(
[(e[0], str(e[1])) for e in filtered_seqs], DNA)
else:
raise ValueError(
'No sequences were remaining in the fasta file. Did you remove all Sample ID\'s?'
)
output_filepath = '%s/%s_sfiltered.fasta' % (dir_path, filename)
output_file = open(output_filepath, 'w')
output_file.write(filtered_seqs.to_fasta())
output_file.close()
def test_call_write_to_file(self):
"""ReferenceRepSetPicker.__call__ otu map correctly written to file"""
app = ReferenceRepSetPicker(params={'Algorithm': 'first',
'ChoiceF': first_id})
app(self.tmp_seq_filepath,
self.tmp_otu_filepath,
self.ref_seq_filepath,
result_path=self.result_filepath)
with open(self.result_filepath) as f:
actual = SequenceCollection.from_fasta_records(parse_fasta(f), DNA)
expected = SequenceCollection.from_fasta_records(
parse_fasta(rep_seqs_reference_result_file_exp.split('\n')), DNA)
# we don't care about order in the results
self.assertEqual(set(actual), set(expected))
def test_degap(self):
"""degap functions as expected
"""
expected = [(id_, seq.replace('.', '').replace('-', ''))
for id_, seq in self.seqs1_t]
expected = SequenceCollection.from_fasta_records(expected, DNASequence)
actual = self.a1.degap()
self.assertEqual(actual, expected)
expected = [(id_, seq.replace('.', '').replace('-', ''))
for id_, seq in self.seqs2_t]
expected = SequenceCollection.from_fasta_records(expected, RNASequence)
actual = self.a2.degap()
self.assertEqual(actual, expected)
def test_degap(self):
"""degap functions as expected
"""
expected = [(id_, seq.replace('.', '').replace('-', ''))
for id_, seq in self.seqs1_t]
expected = SequenceCollection.from_fasta_records(expected, DNASequence)
actual = self.a1.degap()
self.assertEqual(actual, expected)
expected = [(id_, seq.replace('.', '').replace('-', ''))
for id_, seq in self.seqs2_t]
expected = SequenceCollection.from_fasta_records(expected, RNASequence)
actual = self.a2.degap()
self.assertEqual(actual, expected)
def filter_samples(prefs, data, dir_path='', filename=None):
"""processes the filtering of the otus file and representative seq set, then
writes filtered otus and filtered representative seq set files"""
aln = data['aln']
otus = data['otus']
# filter the otus file based on which samples to remove
new_otus_list = filter_otus(otus, prefs)
filtered_otus_output_filepath = '%s/%s_sfiltered_otus.txt' \
% (dir_path, filename)
filtered_otus_output_filepath = open(filtered_otus_output_filepath, 'w')
# Write out a new otus file
for key in (new_otus_list):
filtered_otus_output_filepath.write(key[0])
for j in key[1]:
filtered_otus_output_filepath.write('\t' + str(j))
filtered_otus_output_filepath.write('\n')
filtered_otus_output_filepath.close()
# filter seq set
filtered_seqs, removed_seqs = filter_aln_by_otus(aln, prefs)
# write a fasta containing list of sequences removed from
# representative set
if len(removed_seqs) > 0:
removed_seqs = SequenceCollection.from_fasta_records(
[(e[0], str(e[1])) for e in removed_seqs], DNA)
else:
raise ValueError(
'No sequences were removed. Did you specify the correct Sample ID?')
output_filepath2 = '%s/%s_sremoved.fasta' % (dir_path, filename)
output_file2 = open(output_filepath2, 'w')
output_file2.write(removed_seqs.to_fasta())
output_file2.close()
# write a fasta containing the filtered representative seqs
if len(filtered_seqs) > 0:
filtered_seqs = SequenceCollection.from_fasta_records(
[(e[0], str(e[1])) for e in filtered_seqs], DNA)
else:
raise ValueError(
'No sequences were remaining in the fasta file. Did you remove all Sample ID\'s?')
output_filepath = '%s/%s_sfiltered.fasta' % (dir_path, filename)
output_file = open(output_filepath, 'w')
output_file.write(filtered_seqs.to_fasta())
output_file.close()
def test_call_write_to_file(self):
"""ReferenceRepSetPicker.__call__ otu map correctly written to file"""
app = ReferenceRepSetPicker(params={
'Algorithm': 'first',
'ChoiceF': first_id
})
app(self.tmp_seq_filepath,
self.tmp_otu_filepath,
self.ref_seq_filepath,
result_path=self.result_filepath)
with open(self.result_filepath) as f:
actual = SequenceCollection.from_fasta_records(parse_fasta(f), DNA)
expected = SequenceCollection.from_fasta_records(
parse_fasta(rep_seqs_reference_result_file_exp.split('\n')), DNA)
# we don't care about order in the results
self.assertEqual(set(actual), set(expected))
def test_ne(self):
"""inequality operator functions as expected
"""
self.assertFalse(self.s1 != self.s1)
self.assertTrue(self.s1 != self.s2)
# SequenceCollections with different number of sequences are not equal
self.assertTrue(self.s1 != SequenceCollection([self.d1]))
class FakeSequenceCollection(SequenceCollection):
pass
# SequenceCollections of different types are not equal
self.assertTrue(self.s1 != FakeSequenceCollection([self.d1, self.d2]))
self.assertTrue(self.s1 != Alignment([self.d1, self.d2]))
# SequenceCollections with different sequences are not equal
self.assertTrue(self.s1 != SequenceCollection([self.d1, self.r1]))
def test_distances(self):
"""distances functions as expected
"""
s1 = SequenceCollection([DNA("ACGT", "d1"), DNA("ACGG", "d2")])
expected = [[0, 0.25],
[0.25, 0]]
expected = DistanceMatrix(expected, ['d1', 'd2'])
actual = s1.distances(hamming)
self.assertEqual(actual, expected)
# alt distance function provided
def dumb_distance(s1, s2):
return 42.
expected = [[0, 42.],
[42., 0]]
expected = DistanceMatrix(expected, ['d1', 'd2'])
actual = s1.distances(dumb_distance)
self.assertEqual(actual, expected)
def setUp(self):
fd, self.pynast_test1_input_fp = mkstemp(prefix="PyNastAlignerTests_", suffix=".fasta")
close(fd)
with open(self.pynast_test1_input_fp, "w") as f:
f.write(pynast_test1_input_fasta)
fd, self.pynast_test1_template_fp = mkstemp(prefix="PyNastAlignerTests_", suffix="template.fasta")
close(fd)
with open(self.pynast_test1_template_fp, "w") as f:
f.write(pynast_test1_template_fasta)
fd, self.pynast_test_template_w_dots_fp = mkstemp(prefix="PyNastAlignerTests_", suffix="template.fasta")
close(fd)
with open(self.pynast_test_template_w_dots_fp, "w") as f:
f.write(pynast_test1_template_fasta.replace("-", "."))
fd, self.pynast_test_template_w_u_fp = mkstemp(prefix="PyNastAlignerTests_", suffix="template.fasta")
close(fd)
with open(self.pynast_test_template_w_u_fp, "w") as f:
f.write(pynast_test1_template_fasta.replace("T", "U"))
fd, self.pynast_test_template_w_lower_fp = mkstemp(prefix="PyNastAlignerTests_", suffix="template.fasta")
close(fd)
with open(self.pynast_test_template_w_lower_fp, "w") as f:
f.write(pynast_test1_template_fasta.lower())
# create temp file names (and touch them so we can reliably
# clean them up)
fd, self.result_fp = mkstemp(prefix="PyNastAlignerTests_", suffix=".fasta")
close(fd)
open(self.result_fp, "w").close()
fd, self.failure_fp = mkstemp(prefix="PyNastAlignerTests_", suffix=".fasta")
close(fd)
open(self.failure_fp, "w").close()
fd, self.log_fp = mkstemp(prefix="PyNastAlignerTests_", suffix=".log")
close(fd)
open(self.log_fp, "w").close()
self._paths_to_clean_up = [
self.pynast_test1_input_fp,
self.result_fp,
self.failure_fp,
self.log_fp,
self.pynast_test1_template_fp,
self.pynast_test_template_w_dots_fp,
self.pynast_test_template_w_u_fp,
self.pynast_test_template_w_lower_fp,
]
self.pynast_test1_aligner = PyNastAligner({"template_filepath": self.pynast_test1_template_fp, "min_len": 15})
self.pynast_test1_expected_aln = Alignment.from_fasta_records(parse_fasta(pynast_test1_expected_alignment), DNA)
self.pynast_test1_expected_fail = SequenceCollection.from_fasta_records(
parse_fasta(pynast_test1_expected_failure), DNA
)
def setUp(self):
"""Initialize values to be used in tests
"""
self.d1 = DNASequence('GATTACA', identifier="d1")
self.d2 = DNASequence('TTG', identifier="d2")
self.d1_lower = DNASequence('gattaca', identifier="d1")
self.d2_lower = DNASequence('ttg', identifier="d2")
self.r1 = RNASequence('GAUUACA', identifier="r1")
self.r2 = RNASequence('UUG', identifier="r2")
self.r3 = RNASequence('U-----UGCC--', identifier="r3")
self.i1 = DNASequence('GATXACA', identifier="i1")
self.seqs1 = [self.d1, self.d2]
self.seqs1_lower = [self.d1_lower, self.d2_lower]
self.seqs2 = [self.r1, self.r2, self.r3]
self.seqs3 = self.seqs1 + self.seqs2
self.seqs1_t = [('d1', 'GATTACA'), ('d2', 'TTG')]
self.seqs2_t = [('r1', 'GAUUACA'), ('r2', 'UUG'),
('r3', 'U-----UGCC--')]
self.seqs3_t = self.seqs1_t + self.seqs2_t
self.s1 = SequenceCollection(self.seqs1)
self.s1_lower = SequenceCollection(self.seqs1_lower)
self.s2 = SequenceCollection(self.seqs2)
self.s3 = SequenceCollection(self.seqs3)
self.empty = SequenceCollection([])
self.invalid_s1 = SequenceCollection([self.i1])
def test_split_fasta_equal_num_seqs_per_file(self):
"""split_fasta funcs as expected when equal num seqs go to each file
"""
fd, filename_prefix = mkstemp(dir=get_qiime_temp_dir(),
prefix='split_fasta_tests',
suffix='')
close(fd)
infile = ['>seq1', 'AACCTTAA', '>seq2', 'TTAACC', 'AATTAA',
'>seq3', 'CCTT--AA']
actual = split_fasta(infile, 1, filename_prefix)
actual_seqs = []
for fp in actual:
actual_seqs += list(open(fp))
remove_files(actual)
expected = ['%s.%d.fasta' % (filename_prefix, i) for i in range(3)]
self.assertEqual(actual, expected)
self.assertEqual(
SequenceCollection.from_fasta_records(parse_fasta(infile), DNA),
SequenceCollection.from_fasta_records(parse_fasta(actual_seqs), DNA))
def test_filter_aln_by_otus(self):
"""filter_aln_by_otus: determines which sequences to keep and which
sequences to remove"""
self.sample_to_extract = "SampleA,SampleB"
exp1 = []
exp1.append(("SampleA", "AAAAAAAAAAAAAAA"))
exp2 = []
exp2.append(("SampleB", "CCCCCCC"))
exp2.append(("SampleC", "GGGGGGGGGGGGGG"))
aln = SequenceCollection.from_fasta_records(self.aln, DNA)
obs1, obs2 = filter_aln_by_otus(aln, self.prefs)
self.assertEqual(obs1, exp1)
self.assertEqual(obs2, exp2)
def test_filter_aln_by_otus(self):
"""filter_aln_by_otus: determines which sequences to keep and which
sequences to remove"""
self.sample_to_extract = 'SampleA,SampleB'
exp1 = []
exp1.append(('SampleA', 'AAAAAAAAAAAAAAA'))
exp2 = []
exp2.append(('SampleB', 'CCCCCCC'))
exp2.append(('SampleC', 'GGGGGGGGGGGGGG'))
aln = SequenceCollection.from_fasta_records(self.aln, DNA)
obs1, obs2 = filter_aln_by_otus(aln, self.prefs)
self.assertEqual(obs1, exp1)
self.assertEqual(obs2, exp2)
def main():
"""opens files as necessary based on prefs"""
option_parser, opts, args = parse_command_line_parameters(**script_info)
data = {}
fasta_file = opts.input_fasta_fp
# load the input alignment
data['aln'] = SequenceCollection.from_fasta_records(
parse_fasta(open(fasta_file)), DNA)
# Load the otu file
otu_path = opts.otu_map_fp
otu_f = open(otu_path, 'U')
otus = fields_to_dict(otu_f)
otu_f.close()
data['otus'] = otus
# Determine which which samples to extract from representative seqs
# and from otus file
if opts.samples_to_extract:
prefs = process_extract_samples(opts.samples_to_extract)
filepath = opts.input_fasta_fp
filename = filepath.strip().split('/')[-1]
filename = filename.split('.')[0]
if opts.output_dir:
if os.path.exists(opts.output_dir):
dir_path = opts.output_dir
else:
try:
os.mkdir(opts.output_dir)
dir_path = opts.output_dir
except OSError:
pass
else:
dir_path = './'
try:
action = filter_samples
except NameError:
action = None
# Place this outside try/except so we don't mask NameError in action
if action:
action(prefs, data, dir_path, filename)
def test_call_pynast_test1_file_output_alt_params(self):
"""PyNastAligner writes correct output files when no seqs align
"""
aligner = PyNastAligner({"template_filepath": self.pynast_test1_template_fp, "min_len": 1000})
actual = aligner(
self.pynast_test1_input_fp, result_path=self.result_fp, log_path=self.log_fp, failure_path=self.failure_fp
)
self.assertTrue(actual is None, "Result should be None when result path provided.")
self.assertEqual(getsize(self.result_fp), 0, "No alignable seqs should result in an empty file.")
# all seqs reported to fail
with open(self.failure_fp) as failure_f:
actual_fail = SequenceCollection.from_fasta_records(parse_fasta(failure_f), DNA)
self.assertEqual(actual_fail.sequence_count(), 3)
def test_call_pynast_test1_file_output(self):
"""PyNastAligner writes correct output files for pynast_test1 seqs
"""
# do not collect results; check output files instead
actual = self.pynast_test1_aligner(
self.pynast_test1_input_fp, result_path=self.result_fp, log_path=self.log_fp, failure_path=self.failure_fp
)
self.assertTrue(actual is None, "Result should be None when result path provided.")
expected_aln = self.pynast_test1_expected_aln
with open(self.result_fp) as result_f:
actual_aln = Alignment.from_fasta_records(parse_fasta(result_f), DNA)
self.assertEqual(actual_aln, expected_aln)
with open(self.failure_fp) as failure_f:
actual_fail = SequenceCollection.from_fasta_records(parse_fasta(failure_f), DNA)
self.assertEqual(actual_fail.to_fasta(), self.pynast_test1_expected_fail.to_fasta())
def test_call_pynast_test1_file_output(self):
"""PyNastAligner writes correct output files for pynast_test1 seqs
"""
# do not collect results; check output files instead
actual = self.pynast_test1_aligner(
self.pynast_test1_input_fp, result_path=self.result_fp,
log_path=self.log_fp, failure_path=self.failure_fp)
self.assertTrue(actual is None,
"Result should be None when result path provided.")
expected_aln = self.pynast_test1_expected_aln
with open(self.result_fp) as result_f:
actual_aln = Alignment.from_fasta_records(parse_fasta(
result_f), DNA)
self.assertEqual(actual_aln, expected_aln)
with open(self.failure_fp) as failure_f:
actual_fail = SequenceCollection.from_fasta_records(
parse_fasta(failure_f), DNA)
self.assertEqual(actual_fail.to_fasta(),
self.pynast_test1_expected_fail.to_fasta())
def test_call_pynast_test1_file_output_alt_params(self):
"""PyNastAligner writes correct output files when no seqs align
"""
aligner = PyNastAligner({
'template_filepath': self.pynast_test1_template_fp,
'min_len': 1000})
actual = aligner(
self.pynast_test1_input_fp, result_path=self.result_fp,
log_path=self.log_fp, failure_path=self.failure_fp)
self.assertTrue(actual is None,
"Result should be None when result path provided.")
self.assertEqual(getsize(self.result_fp), 0,
"No alignable seqs should result in an empty file.")
# all seqs reported to fail
with open(self.failure_fp) as failure_f:
actual_fail = SequenceCollection.from_fasta_records(
parse_fasta(failure_f), DNA)
self.assertEqual(actual_fail.sequence_count(), 3)
def test_from_fasta_records(self):
"""Initialization from list of tuples functions as expected
"""
SequenceCollection.from_fasta_records(self.seqs1_t, DNASequence)
SequenceCollection.from_fasta_records(self.seqs2_t, RNASequence)
SequenceCollection.from_fasta_records(self.seqs3_t, NucleotideSequence)
class SequenceCollectionTests(TestCase):
"""Tests of the SequenceCollection class """
def setUp(self):
"""Initialize values to be used in tests
"""
self.d1 = DNASequence('GATTACA', identifier="d1")
self.d2 = DNASequence('TTG', identifier="d2")
self.d1_lower = DNASequence('gattaca', identifier="d1")
self.d2_lower = DNASequence('ttg', identifier="d2")
self.r1 = RNASequence('GAUUACA', identifier="r1")
self.r2 = RNASequence('UUG', identifier="r2")
self.r3 = RNASequence('U-----UGCC--', identifier="r3")
self.i1 = DNASequence('GATXACA', identifier="i1")
self.seqs1 = [self.d1, self.d2]
self.seqs1_lower = [self.d1_lower, self.d2_lower]
self.seqs2 = [self.r1, self.r2, self.r3]
self.seqs3 = self.seqs1 + self.seqs2
self.seqs1_t = [('d1', 'GATTACA'), ('d2', 'TTG')]
self.seqs2_t = [('r1', 'GAUUACA'), ('r2', 'UUG'),
('r3', 'U-----UGCC--')]
self.seqs3_t = self.seqs1_t + self.seqs2_t
self.s1 = SequenceCollection(self.seqs1)
self.s1_lower = SequenceCollection(self.seqs1_lower)
self.s2 = SequenceCollection(self.seqs2)
self.s3 = SequenceCollection(self.seqs3)
self.empty = SequenceCollection([])
self.invalid_s1 = SequenceCollection([self.i1])
def test_init(self):
"""Initialization functions as expected with varied input types
"""
SequenceCollection(self.seqs1)
SequenceCollection(self.seqs2)
SequenceCollection(self.seqs3)
SequenceCollection([])
def test_init_fail(self):
"""initialization with sequences with overlapping identifiers fails
"""
s1 = [self.d1, self.d1]
self.assertRaises(SequenceCollectionError, SequenceCollection, s1)
def test_init_validate(self):
"""initialization with validation functions as expected
"""
SequenceCollection(self.seqs1, validate=True)
SequenceCollection(self.seqs1, validate=True)
# can't validate self.seqs2 as a DNASequence
self.assertRaises(SequenceCollectionError, SequenceCollection,
self.invalid_s1, validate=True)
def test_from_fasta_records(self):
"""Initialization from list of tuples functions as expected
"""
SequenceCollection.from_fasta_records(self.seqs1_t, DNASequence)
SequenceCollection.from_fasta_records(self.seqs2_t, RNASequence)
SequenceCollection.from_fasta_records(self.seqs3_t, NucleotideSequence)
def test_contains(self):
"""in operator functions as expected
"""
self.assertTrue('d1' in self.s1)
self.assertTrue('r2' in self.s2)
self.assertFalse('r2' in self.s1)
def test_eq(self):
"""equality operator functions as expected
"""
self.assertTrue(self.s1 == self.s1)
self.assertFalse(self.s1 == self.s2)
# different objects can be equal
self.assertTrue(self.s1 == SequenceCollection([self.d1, self.d2]))
self.assertTrue(SequenceCollection([self.d1, self.d2]) == self.s1)
# SequenceCollections with different number of sequences are not equal
self.assertFalse(self.s1 == SequenceCollection([self.d1]))
class FakeSequenceCollection(SequenceCollection):
pass
# SequenceCollections of different types are not equal
self.assertFalse(self.s1 == FakeSequenceCollection([self.d1, self.d2]))
self.assertFalse(self.s1 == Alignment([self.d1, self.d2]))
# SequenceCollections with different sequences are not equal
self.assertFalse(self.s1 == SequenceCollection([self.d1, self.r1]))
def test_getitem(self):
"""getitem functions as expected
"""
self.assertEqual(self.s1[0], self.d1)
self.assertEqual(self.s1[1], self.d2)
self.assertEqual(self.s2[0], self.r1)
self.assertEqual(self.s2[1], self.r2)
self.assertRaises(IndexError, self.empty.__getitem__, 0)
self.assertRaises(KeyError, self.empty.__getitem__, '0')
def test_iter(self):
"""iter functions as expected
"""
s1_iter = iter(self.s1)
count = 0
for actual, expected in zip(s1_iter, self.seqs1):
count += 1
self.assertEqual(actual, expected)
self.assertEqual(count, len(self.seqs1))
self.assertRaises(StopIteration, lambda: next(s1_iter))
def test_len(self):
"""len functions as expected
"""
self.assertEqual(len(self.s1), 2)
self.assertEqual(len(self.s2), 3)
self.assertEqual(len(self.s3), 5)
self.assertEqual(len(self.empty), 0)
def test_ne(self):
"""inequality operator functions as expected
"""
self.assertFalse(self.s1 != self.s1)
self.assertTrue(self.s1 != self.s2)
# SequenceCollections with different number of sequences are not equal
self.assertTrue(self.s1 != SequenceCollection([self.d1]))
class FakeSequenceCollection(SequenceCollection):
pass
# SequenceCollections of different types are not equal
self.assertTrue(self.s1 != FakeSequenceCollection([self.d1, self.d2]))
self.assertTrue(self.s1 != Alignment([self.d1, self.d2]))
# SequenceCollections with different sequences are not equal
self.assertTrue(self.s1 !=
SequenceCollection([self.d1, self.r1]))
def test_repr(self):
"""repr functions as expected
"""
self.assertEqual(repr(self.s1),
"<SequenceCollection: n=2; "
"mean +/- std length=5.00 +/- 2.00>")
self.assertEqual(repr(self.s2),
"<SequenceCollection: n=3; "
"mean +/- std length=7.33 +/- 3.68>")
self.assertEqual(repr(self.s3),
"<SequenceCollection: n=5; "
"mean +/- std length=6.40 +/- 3.32>")
self.assertEqual(repr(self.empty),
"<SequenceCollection: n=0; "
"mean +/- std length=0.00 +/- 0.00>")
def test_reversed(self):
"""reversed functions as expected
"""
s1_iter = reversed(self.s1)
count = 0
for actual, expected in zip(s1_iter, self.seqs1[::-1]):
count += 1
self.assertEqual(actual, expected)
self.assertEqual(count, len(self.seqs1))
self.assertRaises(StopIteration, lambda: next(s1_iter))
def test_k_word_frequencies(self):
"""k_word_frequencies functions as expected
"""
expected1 = defaultdict(int)
expected1['A'] = 3/7.
expected1['C'] = 1/7.
expected1['G'] = 1/7.
expected1['T'] = 2/7.
expected2 = defaultdict(int)
expected2['G'] = 1/3.
expected2['T'] = 2/3.
self.assertEqual(self.s1.k_word_frequencies(k=1),
[expected1, expected2])
expected1 = defaultdict(int)
expected1['GAT'] = 1/2.
expected1['TAC'] = 1/2.
expected2 = defaultdict(int)
expected2['TTG'] = 1/1.
self.assertEqual(self.s1.k_word_frequencies(k=3, overlapping=False),
[expected1, expected2])
self.assertEqual(self.empty.k_word_frequencies(k=1), [])
def test_str(self):
"""str functions as expected
"""
exp1 = ">d1\nGATTACA\n>d2\nTTG\n"
self.assertEqual(str(self.s1), exp1)
exp2 = ">r1\nGAUUACA\n>r2\nUUG\n>r3\nU-----UGCC--\n"
self.assertEqual(str(self.s2), exp2)
exp4 = ""
self.assertEqual(str(self.empty), exp4)
def test_distribution_stats(self):
"""distribution_stats functions as expected
"""
actual1 = self.s1.distribution_stats()
self.assertEqual(actual1[0], 2)
self.assertAlmostEqual(actual1[1], 5.0, 3)
self.assertAlmostEqual(actual1[2], 2.0, 3)
actual2 = self.s2.distribution_stats()
self.assertEqual(actual2[0], 3)
self.assertAlmostEqual(actual2[1], 7.333, 3)
self.assertAlmostEqual(actual2[2], 3.682, 3)
actual3 = self.s3.distribution_stats()
self.assertEqual(actual3[0], 5)
self.assertAlmostEqual(actual3[1], 6.400, 3)
self.assertAlmostEqual(actual3[2], 3.323, 3)
actual4 = self.empty.distribution_stats()
self.assertEqual(actual4[0], 0)
self.assertEqual(actual4[1], 0.0)
self.assertEqual(actual4[2], 0.0)
def test_degap(self):
"""degap functions as expected
"""
expected = [(id_, seq.replace('.', '').replace('-', ''))
for id_, seq in self.seqs2_t]
expected = SequenceCollection.from_fasta_records(expected, RNASequence)
actual = self.s2.degap()
self.assertEqual(actual, expected)
def test_get_seq(self):
"""getseq functions asexpected
"""
self.assertEqual(self.s1.get_seq('d1'), self.d1)
self.assertEqual(self.s1.get_seq('d2'), self.d2)
def test_identifiers(self):
"""identifiers functions as expected
"""
self.assertEqual(self.s1.identifiers(), ['d1', 'd2'])
self.assertEqual(self.s2.identifiers(), ['r1', 'r2', 'r3'])
self.assertEqual(self.s3.identifiers(),
['d1', 'd2', 'r1', 'r2', 'r3'])
self.assertEqual(self.empty.identifiers(), [])
def test_int_map(self):
"""int_map functions as expected
"""
expected1 = {"1": self.d1, "2": self.d2}
expected2 = {"1": "d1", "2": "d2"}
self.assertEqual(self.s1.int_map(), (expected1, expected2))
expected1 = {"h-1": self.d1, "h-2": self.d2}
expected2 = {"h-1": "d1", "h-2": "d2"}
self.assertEqual(self.s1.int_map(prefix='h-'), (expected1, expected2))
def test_is_empty(self):
"""is_empty functions as expected
"""
self.assertFalse(self.s1.is_empty())
self.assertFalse(self.s2.is_empty())
self.assertFalse(self.s3.is_empty())
self.assertTrue(self.empty.is_empty())
def test_is_valid(self):
"""is_valid functions as expected
"""
self.assertTrue(self.s1.is_valid())
self.assertTrue(self.s2.is_valid())
self.assertTrue(self.s3.is_valid())
self.assertTrue(self.empty.is_valid())
self.assertFalse(self.invalid_s1.is_valid())
def test_iteritems(self):
"""iteritems functions as expected
"""
self.assertEqual(list(self.s1.iteritems()),
[(s.identifier, s) for s in self.s1])
def test_lower(self):
"""lower functions as expected
"""
self.assertEqual(self.s1.lower(), self.s1_lower)
def test_sequence_count(self):
"""num_seqs functions as expected
"""
self.assertEqual(self.s1.sequence_count(), 2)
self.assertEqual(self.s2.sequence_count(), 3)
self.assertEqual(self.s3.sequence_count(), 5)
self.assertEqual(self.empty.sequence_count(), 0)
def test_sequence_lengths(self):
"""sequence_lengths functions as expected
"""
self.assertEqual(self.s1.sequence_lengths(), [7, 3])
self.assertEqual(self.s2.sequence_lengths(), [7, 3, 12])
self.assertEqual(self.s3.sequence_lengths(), [7, 3, 7, 3, 12])
self.assertEqual(self.empty.sequence_lengths(), [])
def test_to_fasta(self):
"""to_fasta functions as expected
"""
exp1 = ">d1\nGATTACA\n>d2\nTTG\n"
self.assertEqual(self.s1.to_fasta(), exp1)
exp2 = ">r1\nGAUUACA\n>r2\nUUG\n>r3\nU-----UGCC--\n"
self.assertEqual(self.s2.to_fasta(), exp2)
def test_upper(self):
"""upper functions as expected
"""
self.assertEqual(self.s1_lower.upper(), self.s1)
"""AY800210\tArchaea;Euryarchaeota;Halobacteriales;uncultured
EU883771\tArchaea;Euryarchaeota;Methanomicrobiales;Methanomicrobium et rel.
EF503699\tArchaea;Crenarchaeota;uncultured;uncultured
DQ260310\tArchaea;Euryarchaeota;Methanobacteriales;Methanobacterium
EF503697\tArchaea;Crenarchaeota;uncultured;uncultured"""
blast_test_seqs = SequenceCollection.from_fasta_records([
('s1',
'TTCCGGTTGATCCTGCCGGACCCGACTGCTATCCGGATGCGACTAAGCCATGCTAGTCTAACGGATCTTCGGATCCGTGGCATACCGCTCTGTAACACGTAGATAACCTACCCTGAGGTCGGGGAAACTCCCGGGAAACTGGGCCTAATCCCCGATAGATAATTTGTACTGGAATGTCTTTTTATTGAAACCTCCGAGGCCTCAGGATGGGTCTGCGCCAGATTATGGTCGTAGGTGGGGTAACGGCCCACCTAGCCTTTGATCTGTACCGGACATGAGAGTGTGTGCCGGGAGATGGCCACTGAGACAAGGGGCCAGGCCCTACGGGGCGCAGCAGGCGCGAAAACTTCACAATGCCCGCAAGGGTGATGAGGGTATCCGAGTGCTACCTTAGCCGGTAGCTTTTATTCAGTGTAAATAGCTAGATGAATAAGGGGAGGGCAAGGCTGGTGCCAGCCGCCGCGGTAAAACCAGCTCCCGAGTGGTCGGGATTTTTATTGGGCCTAAAGCGTCCGTAGCCGGGCGTGCAAGTCATTGGTTAAATATCGGGTCTTAAGCCCGAACCTGCTAGTGATACTACACGCCTTGGGACCGGAAGAGGCAAATGGTACGTTGAGGGTAGGGGTGAAATCCTGTAATCCCCAACGGACCACCGGTGGCGAAGCTTGTTCAGTCATGAACAACTCTACACAAGGCGATTTGCTGGGACGGATCCGACGGTGAGGGACGAAACCCAGGGGAGCGAGCGGGATTAGATACCCCGGTAGTCCTGGGCGTAAACGATGCGAACTAGGTGTTGGCGGAGCCACGAGCTCTGTCGGTGCCGAAGCGAAGGCGTTAAGTTCGCCGCCAGGGGAGTACGGCCGCAAGGCTGAAACTTAAAGGAATTGGCGGGGGAGCAC'
),
('s2',
'TGGCGTACGGCTCAGTAACACGTGGATAACTTACCCTTAGGACTGGGATAACTCTGGGAAACTGGGGATAATACTGGATATTAGGCTATGCCTGGAATGGTTTGCCTTTGAAATGTTTTTTTTCGCCTAAGGATAGGTCTGCGGCTGATTAGGTCGTTGGTGGGGTAATGGCCCACCAAGCCGATGATCGGTACGGGTTGTGAGAGCAAGGGCCCGGAGATGGAACCTGAGACAAGGTTCCAGACCCTACGGGGTGCAGCAGGCGCGAAACCTCCGCAATGTACGAAAGTGCGACGGGGGGATCCCAAGTGTTATGCTTTTTTGTATGACTTTTCATTAGTGTAAAAAGCTTTTAGAATAAGAGCTGGGCAAGACCGGTGCCAGCCGCCGCGGTAACACCGGCAGCTCGAGTGGTGACCACTTTTATTGGGCTTAAAGCGTTCGTAGCTTGATTTTTAAGTCTCTTGGGAAATCTCACGGCTTAACTGTGAGGCGTCTAAGAGATACTGGGAATCTAGGGACCGGGAGAGGTAAGAGGTACTTCAGGGGTAGAAGTGAAATTCTGTAATCCTTGAGGGACCACCGATGGCGAAGGCATCTTACCAGAACGGCTTCGACAGTGAGGAACGAAAGCTGGGGGAGCGAACGGGATTAGATACCCCGGTAGTCCCAGCCGTAAACTATGCGCGTTAGGTGTGCCTGTAACTACGAGTTACCGGGGTGCCGAAGTGAAAACGTGAAACGTGCCGCCTGGGAAGTACGGTCGCAAGGCTGAAACTTAAAGGAATTGGCGGGGGAGCACCACAACGGGTGGAGCCTGCGGTTTAATTGGACTCAACGCCGGGCAGCTCACCGGATAGGACAGCGGAATGATAGCCGGGCTGAAGACCTTGCTTGACCAGCTGAGA'
),
('s3',
'AAGAATGGGGATAGCATGCGAGTCACGCCGCAATGTGTGGCATACGGCTCAGTAACACGTAGTCAACATGCCCAGAGGACGTGGACACCTCGGGAAACTGAGGATAAACCGCGATAGGCCACTACTTCTGGAATGAGCCATGACCCAAATCTATATGGCCTTTGGATTGGACTGCGGCCGATCAGGCTGTTGGTGAGGTAATGGCCCACCAAACCTGTAACCGGTACGGGCTTTGAGAGAAGGAGCCCGGAGATGGGCACTGAGACAAGGGCCCAGGCCCTATGGGGCGCAGCAGGCACGAAACCTCTGCAATAGGCGAAAGCTTGACAGGGTTACTCTGAGTGATGCCCGCTAAGGGTATCTTTTGGCACCTCTAAAAATGGTGCAGAATAAGGGGTGGGCAAGTCTGGTGTCAGCCGCCGCGGTAATACCAGCACCCCGAGTTGTCGGGACGATTATTGGGCCTAAAGCATCCGTAGCCTGTTCTGCAAGTCCTCCGTTAAATCCACCCGCTTAACGGATGGGCTGCGGAGGATACTGCAGAGCTAGGAGGCGGGAGAGGCAAACGGTACTCAGTGGGTAGGGGTAAAATCCTTTGATCTACTGAAGACCACCAGTGGTGAAGGCGGTTCGCCAGAACGCGCTCGAACGGTGAGGATGAAAGCTGGGGGAGCAAACCGGAATAGATACCCGAGTAATCCCAACTGTAAACGATGGCAACTCGGGGATGGGTTGGCCTCCAACCAACCCCATGGCCGCAGGGAAGCCGTTTAGCTCTCCCGCCTGGGGAATACGGTCCGCAGAATTGAACCTTAAAGGAATTTGGCGGGGAACCCCCACAAGGGGGAAAACCGTGCGGTTCAATTGGAATCCACCCCCCGGAAACTTTACCCGGGCGCG'
),
('s4',
'GATACCCCCGGAAACTGGGGATTATACCGGATATGTGGGGCTGCCTGGAATGGTACCTCATTGAAATGCTCCCGCGCCTAAAGATGGATCTGCCGCAGAATAAGTAGTTTGCGGGGTAAATGGCCACCCAGCCAGTAATCCGTACCGGTTGTGAAAACCAGAACCCCGAGATGGAAACTGAAACAAAGGTTCAAGGCCTACCGGGCACAACAAGCGCCAAAACTCCGCCATGCGAGCCATCGCGACGGGGGAAAACCAAGTACCACTCCTAACGGGGTGGTTTTTCCGAAGTGGAAAAAGCCTCCAGGAATAAGAACCTGGGCCAGAACCGTGGCCAGCCGCCGCCGTTACACCCGCCAGCTCGAGTTGTTGGCCGGTTTTATTGGGGCCTAAAGCCGGTCCGTAGCCCGTTTTGATAAGGTCTCTCTGGTGAAATTCTACAGCTTAACCTGTGGGAATTGCTGGAGGATACTATTCAAGCTTGAAGCCGGGAGAAGCCTGGAAGTACTCCCGGGGGTAAGGGGTGAAATTCTATTATCCCCGGAAGACCAACTGGTGCCGAAGCGGTCCAGCCTGGAACCGAACTTGACCGTGAGTTACGAAAAGCCAAGGGGCGCGGACCGGAATAAAATAACCAGGGTAGTCCTGGCCGTAAACGATGTGAACTTGGTGGTGGGAATGGCTTCGAACTGCCCAATTGCCGAAAGGAAGCTGTAAATTCACCCGCCTTGGAAGTACGGTCGCAAGACTGGAACCTAAAAGGAATTGGCGGGGGGACACCACAACGCGTGGAGCCTGGCGGTTTTATTGGGATTCCACGCAGACATCTCACTCAGGGGCGACAGCAGAAATGATGGGCAGGTTGATGACCTTGCTTGACAAGCTGAAAAGGAGGTGCAT'
),
('s5',
'TAAAATGACTAGCCTGCGAGTCACGCCGTAAGGCGTGGCATACAGGCTCAGTAACACGTAGTCAACATGCCCAAAGGACGTGGATAACCTCGGGAAACTGAGGATAAACCGCGATAGGCCAAGGTTTCTGGAATGAGCTATGGCCGAAATCTATATGGCCTTTGGATTGGACTGCGGCCGATCAGGCTGTTGGTGAGGTAATGGCCCACCAAACCTGTAACCGGTACGGGCTTTGAGAGAAGTAGCCCGGAGATGGGCACTGAGACAAGGGCCCAGGCCCTATGGGGCGCAGCAGGCGCGAAACCTCTGCAATAGGCGAAAGCCTGACAGGGTTACTCTGAGTGATGCCCGCTAAGGGTATCTTTTGGCACCTCTAAAAATGGTGCAGAATAAGGGGTGGGCAAGTCTGGTGTCAGCCGCCGCGGTAATACCAGCACCCCGAGTTGTCGGGACGATTATTGGGCCTAAAGCATCCGTAGCCTGTTCTGCAAGTCCTCCGTTAAATCCACCTGCTCAACGGATGGGCTGCGGAGGATACCGCAGAGCTAGGAGGCGGGAGAGGCAAACGGTACTCAGTGGGTAGGGGTAAAATCCATTGATCTACTGAAGACCACCAGTGGCGAAGGCGGTTTGCCAGAACGCGCTCGACGGTGAGGGATGAAAGCTGGGGGAGCAAACCGGATTAGATACCCGGGGTAGTCCCAGCTGTAAACGGATGCAGACTCGGGTGATGGGGTTGGCTTCCGGCCCAACCCCAATTGCCCCCAGGCGAAGCCCGTTAAGATCTTGCCGCCCTGTCAGATGTCAGGGCCGCCAATACTCGAAACCTTAAAAGGAAATTGGGCGCGGGAAAAGTCACCAAAAGGGGGTTGAAACCCTGCGGGTTATATATTGTAAACC'
),
('s6',
'ATAGTAGGTGATTGCGAAGACCGCGGAACCGGGACCTAGCACCCAGCCTGTACCGAGGGATGGGGAGCTGTGGCGGTCCACCGACGACCCTTTGTGACAGCCGATTCCTACAATCCCAGCAACTGCAATGATCCACTCTAGTCGGCATAACCGGGAATCGTTAACCTGGTAGGGTTCTCTACGTCTGAGTCTACAGCCCAGAGCAGTCAGGCTACTATACGGTTTGCTGCATTGCATAGGCATCGGTCGCGGGCACTCCTCGCGGTTTCAGCTAGGGTTTAAATGGAGGGTCGCTGCATGAGTATGCAAATAGTGCCACTGCTCTGATACAGAGAAGTGTTGATATGACACCTAAGACCTGGTCACAGTTTTAACCTGCCTACGCACACCAGTGTGCTATTGATTAACGATATCGGTAGACACGACCTTGGTAACCTGACTAACCTCATGGAAAGTGACTAGATAAATGGACCGGAGCCAACTTTCACCCGGAAAACGGACCGACGAATCGTCGTAGACTACCGATCTGACAAAATAAGCACGAGGGAGCATGTTTTGCGCAGGCTAGCCTATTCCCACCTCAAGCCTCGAGAACCAAGACGCCTGATCCGGTGCTGCACGAAGGGTCGCCTCTAGGTAAGGAGAGCTGGCATCTCCAGATCCGATATTTTACCCAACCTTTGCGCGCTCAGATTGTTATAGTGAAACGATTTAAGCCTGAACGGAGTTCCGCTCCATATGTGGGTTATATATGTGAGATGTATTAACTTCCGCAGTTGTCTCTTTCGGTGCAGTACGCTTGGTATGTGTCTCAAATAATCGGTATTATAGTGATCTGAGAGGTTTTAAG'
)
], DNA)
blast_reference_seqs = SequenceCollection.from_fasta_records([
('AY800210',
'TTCCGGTTGATCCTGCCGGACCCGACTGCTATCCGGATGCGACTAAGCCATGCTAGTCTAACGGATCTTCGGATCCGTGGCATACCGCTCTGTAACACGTAGATAACCTACCCTGAGGTCGGGGAAACTCCCGGGAAACTGGGCCTAATCCCCGATAGATAATTTGTACTGGAATGTCTTTTTATTGAAACCTCCGAGGCCTCAGGATGGGTCTGCGCCAGATTATGGTCGTAGGTGGGGTAACGGCCCACCTAGCCTTTGATCTGTACCGGACATGAGAGTGTGTGCCGGGAGATGGCCACTGAGACAAGGGGCCAGGCCCTACGGGGCGCAGCAGGCGCGAAAACTTCACAATGCCCGCAAGGGTGATGAGGGTATCCGAGTGCTACCTTAGCCGGTAGCTTTTATTCAGTGTAAATAGCTAGATGAATAAGGGGAGGGCAAGGCTGGTGCCAGCCGCCGCGGTAAAACCAGCTCCCGAGTGGTCGGGATTTTTATTGGGCCTAAAGCGTCCGTAGCCGGGCGTGCAAGTCATTGGTTAAATATCGGGTCTTAAGCCCGAACCTGCTAGTGATACTACACGCCTTGGGACCGGAAGAGGCAAATGGTACGTTGAGGGTAGGGGTGAAATCCTGTAATCCCCAACGGACCACCGGTGGCGAAGCTTGTTCAGTCATGAACAACTCTACACAAGGCGATTTGCTGGGACGGATCCGACGGTGAGGGACGAAACCCAGGGGAGCGAGCGGGATTAGATACCCCGGTAGTCCTGGGCGTAAACGATGCGAACTAGGTGTTGGCGGAGCCACGAGCTCTGTCGGTGCCGAAGCGAAGGCGTTAAGTTCGCCGCCAGGGGAGTACGGCCGCAAGGCTGAAACTTAAAGGAATTGGCGGGGGAGCAC'
),
('EU883771',
def __call__(self, seq_path, result_path=None, log_path=None,
failure_path=None, cmbuild_params=None, cmalign_params=None):
log_params = []
# load candidate sequences
candidate_sequences = dict(parse_fasta(open(seq_path, 'U')))
# load template sequences
try:
info, template_alignment, struct = list(MinimalRfamParser(open(
self.Params['template_filepath'], 'U'),
seq_constructor=ChangedSequence))[0]
except RecordError:
raise ValueError(
"Template alignment must be in Stockholm format with corresponding secondary structure annotation when using InfernalAligner.")
moltype = self.Params['moltype']
# Need to make separate mapping for unaligned sequences
unaligned = SequenceCollection.from_fasta_records(
candidate_sequences.iteritems(), DNASequence)
mapped_seqs, new_to_old_ids = unaligned.int_map(prefix='unaligned_')
mapped_seq_tuples = [(k, str(v)) for k,v in mapped_seqs.iteritems()]
# Turn on --gapthresh option in cmbuild to force alignment to full
# model
if cmbuild_params is None:
cmbuild_params = {}
cmbuild_params.update({'--gapthresh': 1.0})
# record cmbuild parameters
log_params.append('cmbuild parameters:')
log_params.append(str(cmbuild_params))
# Turn on --sub option in Infernal, since we know the unaligned sequences
# are fragments.
# Also turn on --gapthresh to use same gapthresh as was used to build
# model
if cmalign_params is None:
cmalign_params = {}
cmalign_params.update({'--sub': True, '--gapthresh': 1.0})
# record cmalign parameters
log_params.append('cmalign parameters:')
log_params.append(str(cmalign_params))
# Align sequences to alignment including alignment gaps.
aligned, struct_string = cmalign_from_alignment(aln=template_alignment,
structure_string=struct,
seqs=mapped_seq_tuples,
moltype=moltype,
include_aln=True,
params=cmalign_params,
cmbuild_params=cmbuild_params)
# Pull out original sequences from full alignment.
infernal_aligned = []
# Get a dict of the identifiers to sequences (note that this is a
# cogent alignment object, hence the call to NamedSeqs)
aligned_dict = aligned.NamedSeqs
for n, o in new_to_old_ids.iteritems():
aligned_seq = aligned_dict[n]
infernal_aligned.append((o, aligned_seq))
# Create an Alignment object from alignment dict
infernal_aligned = Alignment.from_fasta_records(infernal_aligned, DNASequence)
if log_path is not None:
log_file = open(log_path, 'w')
log_file.write('\n'.join(log_params))
log_file.close()
if result_path is not None:
result_file = open(result_path, 'w')
result_file.write(infernal_aligned.to_fasta())
result_file.close()
return None
else:
try:
return infernal_aligned
except ValueError:
return {}
def test_from_fasta_records(self):
"""Initialization from list of tuples functions as expected
"""
SequenceCollection.from_fasta_records(self.seqs1_t, DNASequence)
SequenceCollection.from_fasta_records(self.seqs2_t, RNASequence)
SequenceCollection.from_fasta_records(self.seqs3_t, NucleotideSequence)
tggctcagattgaacgctggcggcaggcctaacacatgcaagtcgagcggaaacgantnntntgaaccttcggggnacgatnacggcgtcgagcggcggacgggtgagtaatgcctgggaaattgccctgatgtgggggataactattggaaacgatagctaataccgcataatgtctacggaccaaagagggggaccttcgggcctctcgcttcaggatatgcccaggtgggattagctagttggtgaggtaatggctcaccaaggcgacgatccctagctggtctgagaggatgatcagccacactggaactgag
"""
blast_id_to_taxonomy = \
"""AY800210\tArchaea;Euryarchaeota;Halobacteriales;uncultured
EU883771\tArchaea;Euryarchaeota;Methanomicrobiales;Methanomicrobium et rel.
EF503699\tArchaea;Crenarchaeota;uncultured;uncultured
DQ260310\tArchaea;Euryarchaeota;Methanobacteriales;Methanobacterium
EF503697\tArchaea;Crenarchaeota;uncultured;uncultured"""
blast_test_seqs = SequenceCollection.from_fasta_records([
('s1',
'TTCCGGTTGATCCTGCCGGACCCGACTGCTATCCGGATGCGACTAAGCCATGCTAGTCTAACGGATCTTCGGATCCGTGGCATACCGCTCTGTAACACGTAGATAACCTACCCTGAGGTCGGGGAAACTCCCGGGAAACTGGGCCTAATCCCCGATAGATAATTTGTACTGGAATGTCTTTTTATTGAAACCTCCGAGGCCTCAGGATGGGTCTGCGCCAGATTATGGTCGTAGGTGGGGTAACGGCCCACCTAGCCTTTGATCTGTACCGGACATGAGAGTGTGTGCCGGGAGATGGCCACTGAGACAAGGGGCCAGGCCCTACGGGGCGCAGCAGGCGCGAAAACTTCACAATGCCCGCAAGGGTGATGAGGGTATCCGAGTGCTACCTTAGCCGGTAGCTTTTATTCAGTGTAAATAGCTAGATGAATAAGGGGAGGGCAAGGCTGGTGCCAGCCGCCGCGGTAAAACCAGCTCCCGAGTGGTCGGGATTTTTATTGGGCCTAAAGCGTCCGTAGCCGGGCGTGCAAGTCATTGGTTAAATATCGGGTCTTAAGCCCGAACCTGCTAGTGATACTACACGCCTTGGGACCGGAAGAGGCAAATGGTACGTTGAGGGTAGGGGTGAAATCCTGTAATCCCCAACGGACCACCGGTGGCGAAGCTTGTTCAGTCATGAACAACTCTACACAAGGCGATTTGCTGGGACGGATCCGACGGTGAGGGACGAAACCCAGGGGAGCGAGCGGGATTAGATACCCCGGTAGTCCTGGGCGTAAACGATGCGAACTAGGTGTTGGCGGAGCCACGAGCTCTGTCGGTGCCGAAGCGAAGGCGTTAAGTTCGCCGCCAGGGGAGTACGGCCGCAAGGCTGAAACTTAAAGGAATTGGCGGGGGAGCAC'),
('s2',
'TGGCGTACGGCTCAGTAACACGTGGATAACTTACCCTTAGGACTGGGATAACTCTGGGAAACTGGGGATAATACTGGATATTAGGCTATGCCTGGAATGGTTTGCCTTTGAAATGTTTTTTTTCGCCTAAGGATAGGTCTGCGGCTGATTAGGTCGTTGGTGGGGTAATGGCCCACCAAGCCGATGATCGGTACGGGTTGTGAGAGCAAGGGCCCGGAGATGGAACCTGAGACAAGGTTCCAGACCCTACGGGGTGCAGCAGGCGCGAAACCTCCGCAATGTACGAAAGTGCGACGGGGGGATCCCAAGTGTTATGCTTTTTTGTATGACTTTTCATTAGTGTAAAAAGCTTTTAGAATAAGAGCTGGGCAAGACCGGTGCCAGCCGCCGCGGTAACACCGGCAGCTCGAGTGGTGACCACTTTTATTGGGCTTAAAGCGTTCGTAGCTTGATTTTTAAGTCTCTTGGGAAATCTCACGGCTTAACTGTGAGGCGTCTAAGAGATACTGGGAATCTAGGGACCGGGAGAGGTAAGAGGTACTTCAGGGGTAGAAGTGAAATTCTGTAATCCTTGAGGGACCACCGATGGCGAAGGCATCTTACCAGAACGGCTTCGACAGTGAGGAACGAAAGCTGGGGGAGCGAACGGGATTAGATACCCCGGTAGTCCCAGCCGTAAACTATGCGCGTTAGGTGTGCCTGTAACTACGAGTTACCGGGGTGCCGAAGTGAAAACGTGAAACGTGCCGCCTGGGAAGTACGGTCGCAAGGCTGAAACTTAAAGGAATTGGCGGGGGAGCACCACAACGGGTGGAGCCTGCGGTTTAATTGGACTCAACGCCGGGCAGCTCACCGGATAGGACAGCGGAATGATAGCCGGGCTGAAGACCTTGCTTGACCAGCTGAGA'),
('s3',
'AAGAATGGGGATAGCATGCGAGTCACGCCGCAATGTGTGGCATACGGCTCAGTAACACGTAGTCAACATGCCCAGAGGACGTGGACACCTCGGGAAACTGAGGATAAACCGCGATAGGCCACTACTTCTGGAATGAGCCATGACCCAAATCTATATGGCCTTTGGATTGGACTGCGGCCGATCAGGCTGTTGGTGAGGTAATGGCCCACCAAACCTGTAACCGGTACGGGCTTTGAGAGAAGGAGCCCGGAGATGGGCACTGAGACAAGGGCCCAGGCCCTATGGGGCGCAGCAGGCACGAAACCTCTGCAATAGGCGAAAGCTTGACAGGGTTACTCTGAGTGATGCCCGCTAAGGGTATCTTTTGGCACCTCTAAAAATGGTGCAGAATAAGGGGTGGGCAAGTCTGGTGTCAGCCGCCGCGGTAATACCAGCACCCCGAGTTGTCGGGACGATTATTGGGCCTAAAGCATCCGTAGCCTGTTCTGCAAGTCCTCCGTTAAATCCACCCGCTTAACGGATGGGCTGCGGAGGATACTGCAGAGCTAGGAGGCGGGAGAGGCAAACGGTACTCAGTGGGTAGGGGTAAAATCCTTTGATCTACTGAAGACCACCAGTGGTGAAGGCGGTTCGCCAGAACGCGCTCGAACGGTGAGGATGAAAGCTGGGGGAGCAAACCGGAATAGATACCCGAGTAATCCCAACTGTAAACGATGGCAACTCGGGGATGGGTTGGCCTCCAACCAACCCCATGGCCGCAGGGAAGCCGTTTAGCTCTCCCGCCTGGGGAATACGGTCCGCAGAATTGAACCTTAAAGGAATTTGGCGGGGAACCCCCACAAGGGGGAAAACCGTGCGGTTCAATTGGAATCCACCCCCCGGAAACTTTACCCGGGCGCG'),
('s4',
'GATACCCCCGGAAACTGGGGATTATACCGGATATGTGGGGCTGCCTGGAATGGTACCTCATTGAAATGCTCCCGCGCCTAAAGATGGATCTGCCGCAGAATAAGTAGTTTGCGGGGTAAATGGCCACCCAGCCAGTAATCCGTACCGGTTGTGAAAACCAGAACCCCGAGATGGAAACTGAAACAAAGGTTCAAGGCCTACCGGGCACAACAAGCGCCAAAACTCCGCCATGCGAGCCATCGCGACGGGGGAAAACCAAGTACCACTCCTAACGGGGTGGTTTTTCCGAAGTGGAAAAAGCCTCCAGGAATAAGAACCTGGGCCAGAACCGTGGCCAGCCGCCGCCGTTACACCCGCCAGCTCGAGTTGTTGGCCGGTTTTATTGGGGCCTAAAGCCGGTCCGTAGCCCGTTTTGATAAGGTCTCTCTGGTGAAATTCTACAGCTTAACCTGTGGGAATTGCTGGAGGATACTATTCAAGCTTGAAGCCGGGAGAAGCCTGGAAGTACTCCCGGGGGTAAGGGGTGAAATTCTATTATCCCCGGAAGACCAACTGGTGCCGAAGCGGTCCAGCCTGGAACCGAACTTGACCGTGAGTTACGAAAAGCCAAGGGGCGCGGACCGGAATAAAATAACCAGGGTAGTCCTGGCCGTAAACGATGTGAACTTGGTGGTGGGAATGGCTTCGAACTGCCCAATTGCCGAAAGGAAGCTGTAAATTCACCCGCCTTGGAAGTACGGTCGCAAGACTGGAACCTAAAAGGAATTGGCGGGGGGACACCACAACGCGTGGAGCCTGGCGGTTTTATTGGGATTCCACGCAGACATCTCACTCAGGGGCGACAGCAGAAATGATGGGCAGGTTGATGACCTTGCTTGACAAGCTGAAAAGGAGGTGCAT'),
('s5',
'TAAAATGACTAGCCTGCGAGTCACGCCGTAAGGCGTGGCATACAGGCTCAGTAACACGTAGTCAACATGCCCAAAGGACGTGGATAACCTCGGGAAACTGAGGATAAACCGCGATAGGCCAAGGTTTCTGGAATGAGCTATGGCCGAAATCTATATGGCCTTTGGATTGGACTGCGGCCGATCAGGCTGTTGGTGAGGTAATGGCCCACCAAACCTGTAACCGGTACGGGCTTTGAGAGAAGTAGCCCGGAGATGGGCACTGAGACAAGGGCCCAGGCCCTATGGGGCGCAGCAGGCGCGAAACCTCTGCAATAGGCGAAAGCCTGACAGGGTTACTCTGAGTGATGCCCGCTAAGGGTATCTTTTGGCACCTCTAAAAATGGTGCAGAATAAGGGGTGGGCAAGTCTGGTGTCAGCCGCCGCGGTAATACCAGCACCCCGAGTTGTCGGGACGATTATTGGGCCTAAAGCATCCGTAGCCTGTTCTGCAAGTCCTCCGTTAAATCCACCTGCTCAACGGATGGGCTGCGGAGGATACCGCAGAGCTAGGAGGCGGGAGAGGCAAACGGTACTCAGTGGGTAGGGGTAAAATCCATTGATCTACTGAAGACCACCAGTGGCGAAGGCGGTTTGCCAGAACGCGCTCGACGGTGAGGGATGAAAGCTGGGGGAGCAAACCGGATTAGATACCCGGGGTAGTCCCAGCTGTAAACGGATGCAGACTCGGGTGATGGGGTTGGCTTCCGGCCCAACCCCAATTGCCCCCAGGCGAAGCCCGTTAAGATCTTGCCGCCCTGTCAGATGTCAGGGCCGCCAATACTCGAAACCTTAAAAGGAAATTGGGCGCGGGAAAAGTCACCAAAAGGGGGTTGAAACCCTGCGGGTTATATATTGTAAACC'),
('s6', 'ATAGTAGGTGATTGCGAAGACCGCGGAACCGGGACCTAGCACCCAGCCTGTACCGAGGGATGGGGAGCTGTGGCGGTCCACCGACGACCCTTTGTGACAGCCGATTCCTACAATCCCAGCAACTGCAATGATCCACTCTAGTCGGCATAACCGGGAATCGTTAACCTGGTAGGGTTCTCTACGTCTGAGTCTACAGCCCAGAGCAGTCAGGCTACTATACGGTTTGCTGCATTGCATAGGCATCGGTCGCGGGCACTCCTCGCGGTTTCAGCTAGGGTTTAAATGGAGGGTCGCTGCATGAGTATGCAAATAGTGCCACTGCTCTGATACAGAGAAGTGTTGATATGACACCTAAGACCTGGTCACAGTTTTAACCTGCCTACGCACACCAGTGTGCTATTGATTAACGATATCGGTAGACACGACCTTGGTAACCTGACTAACCTCATGGAAAGTGACTAGATAAATGGACCGGAGCCAACTTTCACCCGGAAAACGGACCGACGAATCGTCGTAGACTACCGATCTGACAAAATAAGCACGAGGGAGCATGTTTTGCGCAGGCTAGCCTATTCCCACCTCAAGCCTCGAGAACCAAGACGCCTGATCCGGTGCTGCACGAAGGGTCGCCTCTAGGTAAGGAGAGCTGGCATCTCCAGATCCGATATTTTACCCAACCTTTGCGCGCTCAGATTGTTATAGTGAAACGATTTAAGCCTGAACGGAGTTCCGCTCCATATGTGGGTTATATATGTGAGATGTATTAACTTCCGCAGTTGTCTCTTTCGGTGCAGTACGCTTGGTATGTGTCTCAAATAATCGGTATTATAGTGATCTGAGAGGTTTTAAG')], DNA)
blast_reference_seqs = SequenceCollection.from_fasta_records([
('AY800210',
'TTCCGGTTGATCCTGCCGGACCCGACTGCTATCCGGATGCGACTAAGCCATGCTAGTCTAACGGATCTTCGGATCCGTGGCATACCGCTCTGTAACACGTAGATAACCTACCCTGAGGTCGGGGAAACTCCCGGGAAACTGGGCCTAATCCCCGATAGATAATTTGTACTGGAATGTCTTTTTATTGAAACCTCCGAGGCCTCAGGATGGGTCTGCGCCAGATTATGGTCGTAGGTGGGGTAACGGCCCACCTAGCCTTTGATCTGTACCGGACATGAGAGTGTGTGCCGGGAGATGGCCACTGAGACAAGGGGCCAGGCCCTACGGGGCGCAGCAGGCGCGAAAACTTCACAATGCCCGCAAGGGTGATGAGGGTATCCGAGTGCTACCTTAGCCGGTAGCTTTTATTCAGTGTAAATAGCTAGATGAATAAGGGGAGGGCAAGGCTGGTGCCAGCCGCCGCGGTAAAACCAGCTCCCGAGTGGTCGGGATTTTTATTGGGCCTAAAGCGTCCGTAGCCGGGCGTGCAAGTCATTGGTTAAATATCGGGTCTTAAGCCCGAACCTGCTAGTGATACTACACGCCTTGGGACCGGAAGAGGCAAATGGTACGTTGAGGGTAGGGGTGAAATCCTGTAATCCCCAACGGACCACCGGTGGCGAAGCTTGTTCAGTCATGAACAACTCTACACAAGGCGATTTGCTGGGACGGATCCGACGGTGAGGGACGAAACCCAGGGGAGCGAGCGGGATTAGATACCCCGGTAGTCCTGGGCGTAAACGATGCGAACTAGGTGTTGGCGGAGCCACGAGCTCTGTCGGTGCCGAAGCGAAGGCGTTAAGTTCGCCGCCAGGGGAGTACGGCCGCAAGGCTGAAACTTAAAGGAATTGGCGGGGGAGCAC'),
('EU883771',
'TGGCGTACGGCTCAGTAACACGTGGATAACTTACCCTTAGGACTGGGATAACTCTGGGAAACTGGGGATAATACTGGATATTAGGCTATGCCTGGAATGGTTTGCCTTTGAAATGTTTTTTTTCGCCTAAGGATAGGTCTGCGGCTGATTAGGTCGTTGGTGGGGTAATGGCCCACCAAGCCGATGATCGGTACGGGTTGTGAGAGCAAGGGCCCGGAGATGGAACCTGAGACAAGGTTCCAGACCCTACGGGGTGCAGCAGGCGCGAAACCTCCGCAATGTACGAAAGTGCGACGGGGGGATCCCAAGTGTTATGCTTTTTTGTATGACTTTTCATTAGTGTAAAAAGCTTTTAGAATAAGAGCTGGGCAAGACCGGTGCCAGCCGCCGCGGTAACACCGGCAGCTCGAGTGGTGACCACTTTTATTGGGCTTAAAGCGTTCGTAGCTTGATTTTTAAGTCTCTTGGGAAATCTCACGGCTTAACTGTGAGGCGTCTAAGAGATACTGGGAATCTAGGGACCGGGAGAGGTAAGAGGTACTTCAGGGGTAGAAGTGAAATTCTGTAATCCTTGAGGGACCACCGATGGCGAAGGCATCTTACCAGAACGGCTTCGACAGTGAGGAACGAAAGCTGGGGGAGCGAACGGGATTAGATACCCCGGTAGTCCCAGCCGTAAACTATGCGCGTTAGGTGTGCCTGTAACTACGAGTTACCGGGGTGCCGAAGTGAAAACGTGAAACGTGCCGCCTGGGAAGTACGGTCGCAAGGCTGAAACTTAAAGGAATTGGCGGGGGAGCACCACAACGGGTGGAGCCTGCGGTTTAATTGGACTCAACGCCGGGCAGCTCACCGGATAGGACAGCGGAATGATAGCCGGGCTGAAGACCTTGCTTGACCAGCTGAGA'),
('EF503699',
'AAGAATGGGGATAGCATGCGAGTCACGCCGCAATGTGTGGCATACGGCTCAGTAACACGTAGTCAACATGCCCAGAGGACGTGGACACCTCGGGAAACTGAGGATAAACCGCGATAGGCCACTACTTCTGGAATGAGCCATGACCCAAATCTATATGGCCTTTGGATTGGACTGCGGCCGATCAGGCTGTTGGTGAGGTAATGGCCCACCAAACCTGTAACCGGTACGGGCTTTGAGAGAAGGAGCCCGGAGATGGGCACTGAGACAAGGGCCCAGGCCCTATGGGGCGCAGCAGGCACGAAACCTCTGCAATAGGCGAAAGCTTGACAGGGTTACTCTGAGTGATGCCCGCTAAGGGTATCTTTTGGCACCTCTAAAAATGGTGCAGAATAAGGGGTGGGCAAGTCTGGTGTCAGCCGCCGCGGTAATACCAGCACCCCGAGTTGTCGGGACGATTATTGGGCCTAAAGCATCCGTAGCCTGTTCTGCAAGTCCTCCGTTAAATCCACCCGCTTAACGGATGGGCTGCGGAGGATACTGCAGAGCTAGGAGGCGGGAGAGGCAAACGGTACTCAGTGGGTAGGGGTAAAATCCTTTGATCTACTGAAGACCACCAGTGGTGAAGGCGGTTCGCCAGAACGCGCTCGAACGGTGAGGATGAAAGCTGGGGGAGCAAACCGGAATAGATACCCGAGTAATCCCAACTGTAAACGATGGCAACTCGGGGATGGGTTGGCCTCCAACCAACCCCATGGCCGCAGGGAAGCCGTTTAGCTCTCCCGCCTGGGGAATACGGTCCGCAGAATTGAACCTTAAAGGAATTTGGCGGGGAACCCCCACAAGGGGGAAAACCGTGCGGTTCAATTGGAATCCACCCCCCGGAAACTTTACCCGGGCGCG'),
('DQ260310',
def setUp(self):
fd, self.pynast_test1_input_fp = mkstemp(
prefix='PyNastAlignerTests_', suffix='.fasta')
close(fd)
with open(self.pynast_test1_input_fp, 'w') as f:
f.write(pynast_test1_input_fasta)
fd, self.pynast_test1_template_fp = mkstemp(
prefix='PyNastAlignerTests_', suffix='template.fasta')
close(fd)
with open(self.pynast_test1_template_fp, 'w') as f:
f.write(pynast_test1_template_fasta)
fd, self.pynast_test_template_w_dots_fp = mkstemp(
prefix='PyNastAlignerTests_', suffix='template.fasta')
close(fd)
with open(self.pynast_test_template_w_dots_fp, 'w') as f:
f.write(pynast_test1_template_fasta.replace('-', '.'))
fd, self.pynast_test_template_w_u_fp = mkstemp(
prefix='PyNastAlignerTests_', suffix='template.fasta')
close(fd)
with open(self.pynast_test_template_w_u_fp, 'w') as f:
f.write(pynast_test1_template_fasta.replace('T', 'U'))
fd, self.pynast_test_template_w_lower_fp = mkstemp(
prefix='PyNastAlignerTests_', suffix='template.fasta')
close(fd)
with open(self.pynast_test_template_w_lower_fp, 'w') as f:
f.write(pynast_test1_template_fasta.lower())
# create temp file names (and touch them so we can reliably
# clean them up)
fd, self.result_fp = mkstemp(
prefix='PyNastAlignerTests_', suffix='.fasta')
close(fd)
open(self.result_fp, 'w').close()
fd, self.failure_fp = mkstemp(
prefix='PyNastAlignerTests_', suffix='.fasta')
close(fd)
open(self.failure_fp, 'w').close()
fd, self.log_fp = mkstemp(
prefix='PyNastAlignerTests_', suffix='.log')
close(fd)
open(self.log_fp, 'w').close()
self._paths_to_clean_up = [
self.pynast_test1_input_fp,
self.result_fp,
self.failure_fp,
self.log_fp,
self.pynast_test1_template_fp,
self.pynast_test_template_w_dots_fp,
self.pynast_test_template_w_u_fp,
self.pynast_test_template_w_lower_fp
]
self.pynast_test1_aligner = PyNastAligner({
'template_filepath': self.pynast_test1_template_fp,
'min_len': 15,
})
self.pynast_test1_expected_aln = Alignment.from_fasta_records(
parse_fasta(pynast_test1_expected_alignment),
DNA)
self.pynast_test1_expected_fail = SequenceCollection.from_fasta_records(
parse_fasta(pynast_test1_expected_failure), DNA)
def setUp(self):
"""Initialize values to be used in tests
"""
self.d1 = DNASequence('GATTACA', id="d1")
self.d2 = DNASequence('TTG', id="d2")
self.d1_lower = DNASequence('gattaca', id="d1")
self.d2_lower = DNASequence('ttg', id="d2")
self.r1 = RNASequence('GAUUACA', id="r1")
self.r2 = RNASequence('UUG', id="r2")
self.r3 = RNASequence('U-----UGCC--', id="r3")
self.i1 = DNASequence('GATXACA', id="i1")
self.seqs1 = [self.d1, self.d2]
self.seqs1_lower = [self.d1_lower, self.d2_lower]
self.seqs2 = [self.r1, self.r2, self.r3]
self.seqs3 = self.seqs1 + self.seqs2
self.seqs1_t = [('d1', 'GATTACA'), ('d2', 'TTG')]
self.seqs2_t = [('r1', 'GAUUACA'), ('r2', 'UUG'),
('r3', 'U-----UGCC--')]
self.seqs3_t = self.seqs1_t + self.seqs2_t
self.s1 = SequenceCollection(self.seqs1)
self.s1_lower = SequenceCollection(self.seqs1_lower)
self.s2 = SequenceCollection(self.seqs2)
self.s3 = SequenceCollection(self.seqs3)
self.empty = SequenceCollection([])
self.invalid_s1 = SequenceCollection([self.i1])
class SequenceCollectionTests(TestCase):
"""Tests of the SequenceCollection class """
def setUp(self):
"""Initialize values to be used in tests
"""
self.d1 = DNASequence('GATTACA', id="d1")
self.d2 = DNASequence('TTG', id="d2")
self.d1_lower = DNASequence('gattaca', id="d1")
self.d2_lower = DNASequence('ttg', id="d2")
self.r1 = RNASequence('GAUUACA', id="r1")
self.r2 = RNASequence('UUG', id="r2")
self.r3 = RNASequence('U-----UGCC--', id="r3")
self.i1 = DNASequence('GATXACA', id="i1")
self.seqs1 = [self.d1, self.d2]
self.seqs1_lower = [self.d1_lower, self.d2_lower]
self.seqs2 = [self.r1, self.r2, self.r3]
self.seqs3 = self.seqs1 + self.seqs2
self.seqs1_t = [('d1', 'GATTACA'), ('d2', 'TTG')]
self.seqs2_t = [('r1', 'GAUUACA'), ('r2', 'UUG'),
('r3', 'U-----UGCC--')]
self.seqs3_t = self.seqs1_t + self.seqs2_t
self.s1 = SequenceCollection(self.seqs1)
self.s1_lower = SequenceCollection(self.seqs1_lower)
self.s2 = SequenceCollection(self.seqs2)
self.s3 = SequenceCollection(self.seqs3)
self.empty = SequenceCollection([])
self.invalid_s1 = SequenceCollection([self.i1])
def test_init(self):
"""Initialization functions as expected with varied input types
"""
SequenceCollection(self.seqs1)
SequenceCollection(self.seqs2)
SequenceCollection(self.seqs3)
SequenceCollection([])
def test_init_fail(self):
"""initialization with sequences with overlapping ids fails
"""
s1 = [self.d1, self.d1]
self.assertRaises(SequenceCollectionError, SequenceCollection, s1)
def test_init_validate(self):
"""initialization with validation functions as expected
"""
SequenceCollection(self.seqs1, validate=True)
SequenceCollection(self.seqs1, validate=True)
# can't validate self.seqs2 as a DNASequence
self.assertRaises(SequenceCollectionError,
SequenceCollection,
self.invalid_s1,
validate=True)
def test_from_fasta_records(self):
"""Initialization from list of tuples functions as expected
"""
SequenceCollection.from_fasta_records(self.seqs1_t, DNASequence)
SequenceCollection.from_fasta_records(self.seqs2_t, RNASequence)
SequenceCollection.from_fasta_records(self.seqs3_t, NucleotideSequence)
def test_contains(self):
"""in operator functions as expected
"""
self.assertTrue('d1' in self.s1)
self.assertTrue('r2' in self.s2)
self.assertFalse('r2' in self.s1)
def test_eq(self):
"""equality operator functions as expected
"""
self.assertTrue(self.s1 == self.s1)
self.assertFalse(self.s1 == self.s2)
# different objects can be equal
self.assertTrue(self.s1 == SequenceCollection([self.d1, self.d2]))
self.assertTrue(SequenceCollection([self.d1, self.d2]) == self.s1)
# SequenceCollections with different number of sequences are not equal
self.assertFalse(self.s1 == SequenceCollection([self.d1]))
class FakeSequenceCollection(SequenceCollection):
pass
# SequenceCollections of different types are not equal
self.assertFalse(self.s1 == FakeSequenceCollection([self.d1, self.d2]))
self.assertFalse(self.s1 == Alignment([self.d1, self.d2]))
# SequenceCollections with different sequences are not equal
self.assertFalse(self.s1 == SequenceCollection([self.d1, self.r1]))
def test_getitem(self):
"""getitem functions as expected
"""
self.assertEqual(self.s1[0], self.d1)
self.assertEqual(self.s1[1], self.d2)
self.assertEqual(self.s2[0], self.r1)
self.assertEqual(self.s2[1], self.r2)
self.assertRaises(IndexError, self.empty.__getitem__, 0)
self.assertRaises(KeyError, self.empty.__getitem__, '0')
def test_iter(self):
"""iter functions as expected
"""
s1_iter = iter(self.s1)
count = 0
for actual, expected in zip(s1_iter, self.seqs1):
count += 1
self.assertEqual(actual, expected)
self.assertEqual(count, len(self.seqs1))
self.assertRaises(StopIteration, lambda: next(s1_iter))
def test_len(self):
"""len functions as expected
"""
self.assertEqual(len(self.s1), 2)
self.assertEqual(len(self.s2), 3)
self.assertEqual(len(self.s3), 5)
self.assertEqual(len(self.empty), 0)
def test_ne(self):
"""inequality operator functions as expected
"""
self.assertFalse(self.s1 != self.s1)
self.assertTrue(self.s1 != self.s2)
# SequenceCollections with different number of sequences are not equal
self.assertTrue(self.s1 != SequenceCollection([self.d1]))
class FakeSequenceCollection(SequenceCollection):
pass
# SequenceCollections of different types are not equal
self.assertTrue(self.s1 != FakeSequenceCollection([self.d1, self.d2]))
self.assertTrue(self.s1 != Alignment([self.d1, self.d2]))
# SequenceCollections with different sequences are not equal
self.assertTrue(self.s1 != SequenceCollection([self.d1, self.r1]))
def test_repr(self):
"""repr functions as expected
"""
self.assertEqual(
repr(self.s1), "<SequenceCollection: n=2; "
"mean +/- std length=5.00 +/- 2.00>")
self.assertEqual(
repr(self.s2), "<SequenceCollection: n=3; "
"mean +/- std length=7.33 +/- 3.68>")
self.assertEqual(
repr(self.s3), "<SequenceCollection: n=5; "
"mean +/- std length=6.40 +/- 3.32>")
self.assertEqual(
repr(self.empty), "<SequenceCollection: n=0; "
"mean +/- std length=0.00 +/- 0.00>")
def test_reversed(self):
"""reversed functions as expected
"""
s1_iter = reversed(self.s1)
count = 0
for actual, expected in zip(s1_iter, self.seqs1[::-1]):
count += 1
self.assertEqual(actual, expected)
self.assertEqual(count, len(self.seqs1))
self.assertRaises(StopIteration, lambda: next(s1_iter))
def test_k_word_frequencies(self):
"""k_word_frequencies functions as expected
"""
expected1 = defaultdict(int)
expected1['A'] = 3 / 7.
expected1['C'] = 1 / 7.
expected1['G'] = 1 / 7.
expected1['T'] = 2 / 7.
expected2 = defaultdict(int)
expected2['G'] = 1 / 3.
expected2['T'] = 2 / 3.
self.assertEqual(self.s1.k_word_frequencies(k=1),
[expected1, expected2])
expected1 = defaultdict(int)
expected1['GAT'] = 1 / 2.
expected1['TAC'] = 1 / 2.
expected2 = defaultdict(int)
expected2['TTG'] = 1 / 1.
self.assertEqual(self.s1.k_word_frequencies(k=3, overlapping=False),
[expected1, expected2])
self.assertEqual(self.empty.k_word_frequencies(k=1), [])
def test_str(self):
"""str functions as expected
"""
exp1 = ">d1\nGATTACA\n>d2\nTTG\n"
self.assertEqual(str(self.s1), exp1)
exp2 = ">r1\nGAUUACA\n>r2\nUUG\n>r3\nU-----UGCC--\n"
self.assertEqual(str(self.s2), exp2)
exp4 = ""
self.assertEqual(str(self.empty), exp4)
def test_distribution_stats(self):
"""distribution_stats functions as expected
"""
actual1 = self.s1.distribution_stats()
self.assertEqual(actual1[0], 2)
self.assertAlmostEqual(actual1[1], 5.0, 3)
self.assertAlmostEqual(actual1[2], 2.0, 3)
actual2 = self.s2.distribution_stats()
self.assertEqual(actual2[0], 3)
self.assertAlmostEqual(actual2[1], 7.333, 3)
self.assertAlmostEqual(actual2[2], 3.682, 3)
actual3 = self.s3.distribution_stats()
self.assertEqual(actual3[0], 5)
self.assertAlmostEqual(actual3[1], 6.400, 3)
self.assertAlmostEqual(actual3[2], 3.323, 3)
actual4 = self.empty.distribution_stats()
self.assertEqual(actual4[0], 0)
self.assertEqual(actual4[1], 0.0)
self.assertEqual(actual4[2], 0.0)
def test_degap(self):
"""degap functions as expected
"""
expected = [(id_, seq.replace('.', '').replace('-', ''))
for id_, seq in self.seqs2_t]
expected = SequenceCollection.from_fasta_records(expected, RNASequence)
actual = self.s2.degap()
self.assertEqual(actual, expected)
def test_get_seq(self):
"""getseq functions asexpected
"""
self.assertEqual(self.s1.get_seq('d1'), self.d1)
self.assertEqual(self.s1.get_seq('d2'), self.d2)
def test_ids(self):
"""ids functions as expected
"""
self.assertEqual(self.s1.ids(), ['d1', 'd2'])
self.assertEqual(self.s2.ids(), ['r1', 'r2', 'r3'])
self.assertEqual(self.s3.ids(), ['d1', 'd2', 'r1', 'r2', 'r3'])
self.assertEqual(self.empty.ids(), [])
def test_int_map(self):
"""int_map functions as expected
"""
expected1 = {"1": self.d1, "2": self.d2}
expected2 = {"1": "d1", "2": "d2"}
self.assertEqual(self.s1.int_map(), (expected1, expected2))
expected1 = {"h-1": self.d1, "h-2": self.d2}
expected2 = {"h-1": "d1", "h-2": "d2"}
self.assertEqual(self.s1.int_map(prefix='h-'), (expected1, expected2))
def test_is_empty(self):
"""is_empty functions as expected
"""
self.assertFalse(self.s1.is_empty())
self.assertFalse(self.s2.is_empty())
self.assertFalse(self.s3.is_empty())
self.assertTrue(self.empty.is_empty())
def test_is_valid(self):
"""is_valid functions as expected
"""
self.assertTrue(self.s1.is_valid())
self.assertTrue(self.s2.is_valid())
self.assertTrue(self.s3.is_valid())
self.assertTrue(self.empty.is_valid())
self.assertFalse(self.invalid_s1.is_valid())
def test_iteritems(self):
"""iteritems functions as expected
"""
self.assertEqual(list(self.s1.iteritems()),
[(s.id, s) for s in self.s1])
def test_lower(self):
"""lower functions as expected
"""
self.assertEqual(self.s1.lower(), self.s1_lower)
def test_sequence_count(self):
"""num_seqs functions as expected
"""
self.assertEqual(self.s1.sequence_count(), 2)
self.assertEqual(self.s2.sequence_count(), 3)
self.assertEqual(self.s3.sequence_count(), 5)
self.assertEqual(self.empty.sequence_count(), 0)
def test_sequence_lengths(self):
"""sequence_lengths functions as expected
"""
self.assertEqual(self.s1.sequence_lengths(), [7, 3])
self.assertEqual(self.s2.sequence_lengths(), [7, 3, 12])
self.assertEqual(self.s3.sequence_lengths(), [7, 3, 7, 3, 12])
self.assertEqual(self.empty.sequence_lengths(), [])
def test_to_fasta(self):
"""to_fasta functions as expected
"""
exp1 = ">d1\nGATTACA\n>d2\nTTG\n"
self.assertEqual(self.s1.to_fasta(), exp1)
exp2 = ">r1\nGAUUACA\n>r2\nUUG\n>r3\nU-----UGCC--\n"
self.assertEqual(self.s2.to_fasta(), exp2)
def test_upper(self):
"""upper functions as expected
"""
self.assertEqual(self.s1_lower.upper(), self.s1)
