def test_constructor_interval_metadata_len(self):
for n in 1, 2, 3:
im = IntervalMetadata(n)
im.add([(0, 1)], metadata={'a': 'b'})
obj = self._interval_metadata_constructor_(n, im)
self.assertTrue(obj.has_interval_metadata())
self.assertIsInstance(obj.interval_metadata, IntervalMetadata)
def _parse_record(lines):
sid = lines[0].split()[1]
splitter = split(split_head, is_head=lambda s: not s.startswith(' '))
imd = IntervalMetadata(None)
for gene in splitter(lines):
if len(gene) == 1:
# there is no terminator predicted
continue
gene_id = gene[0].split()[0]
it = iter(gene[1:])
for term in it:
items = term.split()
term_id = '%s_%s' % (items[0], items[1])
hair_pin_seq = next(it)
hair_pin_seq = '/'.join(hair_pin_seq.split())
start, end = int(items[2]), int(items[4])
strand = items[5]
if strand == '-':
start, end = end, start
bounds = [(start, end)]
md = {
'ID': term_id,
'gene_id': gene_id,
'confidence': items[7],
'strand': strand,
'source': 'TransTermHP',
'sequence': hair_pin_seq,
'type': 'terminator'
}
imd.add(bounds, metadata=md)
return sid, imd
def test_ne_diff_bounds(self):
im1 = IntervalMetadata(10)
im2 = IntervalMetadata(9)
intvl = {'bounds': [(0, 1)], 'metadata': {'spam': 'foo'}}
im1.add(**intvl)
im2.add(**intvl)
self.assertReallyNotEqual(im1, im2)
def test_ne_diff_bounds(self):
im1 = IntervalMetadata(10)
im2 = IntervalMetadata(9)
intvl = {'bounds': [(0, 1)], 'metadata': {'spam': 'foo'}}
im1.add(**intvl)
im2.add(**intvl)
self.assertReallyNotEqual(im1, im2)
def test_init_copy_from(self):
for i in [None, 99, 999]:
obs = IntervalMetadata(i, self.im_1)
exp = IntervalMetadata(i)
exp.add(bounds=[(1, 2), (4, self.upper_bound)],
metadata={'gene': 'sagA', 'bound': 0})
self.assertEqual(obs, exp)
def test_complement_without_reverse_non_empty(self):
for (constructor, seq_str, comp_str,
qual) in self.all_combos_comp_qual:
comp = constructor(seq_str).complement()
self.assertEqual(comp, constructor(comp_str))
im = IntervalMetadata(len(seq_str))
im.add([(0, 1)], metadata={'gene': 'p53'})
comp = constructor(seq_str,
metadata={
'id': 'foo',
'description': 'bar'
},
positional_metadata={
'quality': qual
},
interval_metadata=im).complement()
self.assertEqual(
comp,
constructor(comp_str,
metadata={
'id': 'foo',
'description': 'bar'
},
positional_metadata={'quality': qual},
interval_metadata=im))
def test_compute_trna_score(self):
imd = IntervalMetadata(None)
obs = compute_trna_score([imd])
self.assertEqual(obs, 0.1)
for a in [
'Cys', 'Gln', 'Glu', 'Gly', 'His', 'Ile', 'Leu', 'Lys', 'Met',
'Phe', 'Pro', 'Ser', 'Thr', 'Trp', 'Tyr', 'Val'
]:
imd.add([(0, 12)],
metadata={
'type': 'tRNA',
'product': 'tRNA-' + a
})
obs = compute_trna_score([imd])
self.assertEqual(obs, 0.6)
for a in ['Ala', 'Arg', 'Asn', 'Asp']:
imd.add([(0, 12)],
metadata={
'type': 'tRNA',
'product': 'tRNA-' + a
})
obs = compute_trna_score([imd])
self.assertEqual(obs, 1)
def test_complement_with_reverse_non_empty(self):
for (constructor, seq_str, rev_comp_str,
qual) in self.all_combos_rev_comp_qual:
rc = constructor(seq_str).complement(reverse=True)
self.assertEqual(rc, constructor(rev_comp_str))
length = len(seq_str)
im = IntervalMetadata(length)
im.add([(0, 1)], metadata={'gene': 'p53'})
im_rc = IntervalMetadata(length)
im_rc.add([(length - 1, length)], metadata={'gene': 'p53'})
original = constructor(seq_str,
metadata={
'id': 'foo',
'description': 'bar'
},
positional_metadata={'quality': qual},
interval_metadata=im)
rc = original.complement(reverse=True)
self.assertEqual(
rc,
constructor(rev_comp_str,
metadata={
'id': 'foo',
'description': 'bar'
},
positional_metadata={'quality': list(qual)[::-1]},
interval_metadata=im_rc))
# assert the original object is not changed
self.assertIsNot(original.interval_metadata, im)
self.assertEqual(original.interval_metadata, im)
def _parse_record(lines):
imd = IntervalMetadata(None)
seq_id = lines[0].split('\t')[0]
for line in lines:
bounds, md = _parse_line(line)
imd.add(bounds, metadata=md)
return seq_id, imd
def test_complement_with_reverse_non_empty(self):
for (constructor, seq_str, rev_comp_str,
qual) in self.all_combos_rev_comp_qual:
rc = constructor(seq_str).complement(reverse=True)
self.assertEqual(rc, constructor(rev_comp_str))
length = len(seq_str)
im = IntervalMetadata(length)
im.add([(0, 1)], metadata={'gene': 'p53'})
im_rc = IntervalMetadata(length)
im_rc.add([(length-1, length)], metadata={'gene': 'p53'})
original = constructor(
seq_str,
metadata={'id': 'foo', 'description': 'bar'},
positional_metadata={
'quality': qual},
interval_metadata=im)
rc = original.complement(reverse=True)
self.assertEqual(
rc,
constructor(
rev_comp_str,
metadata={'id': 'foo', 'description': 'bar'},
positional_metadata={'quality':
list(qual)[::-1]},
interval_metadata=im_rc))
# assert the original object is not changed
self.assertIsNot(original.interval_metadata, im)
self.assertEqual(original.interval_metadata, im)
def test_create_faa(self):
imd = IntervalMetadata(None)
imd.add([(0, 120)],
metadata={
'type': 'CDS',
'product': 'Homoserine kinase',
'ID': '1_1'
})
seq = DNA(
'ATGGTTAAAGTTTATGCCCCGGCTTCCAGTGCCAATATGAGCGTCGGGTTTGATGTGCTC'
'GGGGCGGCGGTGACACCCGTTGATGGTGCATTGCTCGGAGATGTAGTCACGGTTGAGGCG'
'GCAGAGACATTCAGTCTCAACAACCTCGGACGCTTTGCCGATAAGCTGCCGTCAGAACCA'
'CGGGAAAATATCGTTTATCAGTGCTGGGAGCGTTTTTGCCTGGAGCTGGGCAAGCAAATT'
'CCAGTGGCGATGACTCTGGAAAAGAATATGCCGATCGGCTCGGGCTTAGGCTCCAGCGCC'
'TGTTCGGTGGTCGCGGCGCTGATGGCGATGAATGAACACTGCGGCAAGCCACTTAATGAC'
'ACCCGTTTGCTGGCTTTGATGGGCGAGCTGGAAGGACGTATCTCCGGCAGCATTCATTAC'
'GACAACGTGGCACCGTGTTTTCTTGGTGGTATGCAGTTGATGATCGAAGAAAACGACATC'
'ATCAGCCAGCAAGTGCCAGGGTTTGATGAGTGGCTGTGGGTGCTGGCGTATCCGGGAATT'
'AAAGTCTCGACGGCAGAAGCCCGGGCTATTTTACCGGCGCAGTATCGCCGCCAGGATTGC'
'ATTGCGCACGGGCGACATCTGGCTGGCTTCATTCACGCCTGCTATTCCCGTCAGCCTGAG'
'CTTGCCGCGAAGCTGATGAAAGATGTTATCGCTGAACCCTACCGTGAACGGTTACTGCCT'
'GGCTTCCGGCAGGCGCGGCAGGCGGTCGCGGAAATCGGCGCGGTAGCGAGCGGTATCTCC'
'GGCTCCGGCCCGACCTTGTTCGCTCTATGTGACAAGCCGGATACCGCCCAGCGCGTTGCC'
'GACTGGTTGGGTAAGAACTACCTGCAAAATCAGGAAGGTTTTGTTCATATTTGCCGGCTG'
'GATACGGCGGGCGCACGAGTACTGGAAAACTAA',
interval_metadata=imd)
create_faa([seq], self.o)
exp = '>1_1 Homoserine kinase\nMVKVYAPASSANMSVGFDVLGAAVTPVDGALLGDVVTVEA\n'
with open(self.o) as out:
obs = out.read()
self.assertEqual(exp, obs)
def _parse_record(lines):
'''Return interval metadata.'''
imd = IntervalMetadata(None)
for line in lines:
bounds, md = _parse_line(line)
imd.add(bounds, metadata=md)
return imd
def test_raise_subregion(self):
im = IntervalMetadata(None)
im.add([(0, 3), (7, 9)], metadata={'type': 'gene'})
with io.StringIO() as fh:
with self.assertRaises(GFF3FormatError):
_serialize_interval_metadata(
im, seq_id='a', fh=fh, skip_subregion=False)
def _parse_record(lines, length):
'''Parse the lines into a IntervalMetadata object.'''
interval_metadata = IntervalMetadata(length)
for line in lines:
columns = line.split('\t')
# there should be 9 columns
if len(columns) != 9:
raise GFF3FormatError(
'do not have 9 columns in this line: "%s"' % line)
# the 1st column is seq ID for every feature. don't store
# this repetitive information
metadata = {'source': columns[1],
'type': columns[2],
'score': columns[5],
'strand': columns[6]}
phase = columns[7]
# phase value can only be int or '.'
try:
metadata['phase'] = int(phase)
except ValueError:
if phase != '.':
raise GFF3FormatError(
'unknown value for phase column: {!r}'.format(phase))
metadata.update(_parse_attr(columns[8]))
start, end = columns[3:5]
bounds = [(int(start)-1, int(end))]
interval_metadata.add(bounds, metadata=metadata)
return interval_metadata
def _parse_record(lines, length):
'''Parse the lines into a IntervalMetadata object.'''
interval_metadata = IntervalMetadata(length)
for line in lines:
columns = line.split('\t')
# there should be 9 columns
if len(columns) != 9:
raise GFF3FormatError('do not have 9 columns in this line: "%s"' %
line)
# the 1st column is seq ID for every feature. don't store
# this repetitive information
metadata = {
'source': columns[1],
'type': columns[2],
'score': columns[5],
'strand': columns[6]
}
phase = columns[7]
# phase value can only be int or '.'
try:
metadata['phase'] = int(phase)
except ValueError:
if phase != '.':
raise GFF3FormatError(
'unknown value for phase column: {!r}'.format(phase))
metadata.update(_parse_attr(columns[8]))
start, end = columns[3:5]
bounds = [(int(start) - 1, int(end))]
interval_metadata.add(bounds, metadata=metadata)
return interval_metadata
def _parse_record(lines):
'''Return interval metadata'''
imd = IntervalMetadata(None)
seq_id = lines[0].split()[2]
for line in lines:
bounds, md = _parse_line(line)
imd.add(bounds, metadata=md)
return seq_id, imd
def test_ne_only_one_is_empty(self):
im1 = IntervalMetadata(self.upper_bound)
im1.add(**self.intvls[0])
obj1 = self._interval_metadata_constructor_(self.upper_bound, im1)
obj2 = self._interval_metadata_constructor_(self.upper_bound)
self.assertReallyNotEqual(obj1, obj2)
def test_upper_bound_is_none(self):
im = IntervalMetadata(None)
# should not raise error
im.add([(0, 1000000000)])
self.assertIsNone(im.upper_bound)
with self.assertRaisesRegex(TypeError, 'upper bound is `None`'):
im._reverse()
with self.assertRaisesRegex(TypeError, 'upper bound is `None`'):
IntervalMetadata.concat([self.im_1, im])
def test_eq_populated_differently(self):
im1 = IntervalMetadata(self.upper_bound)
im1.add(**self.intvls[0])
obj1 = self._interval_metadata_constructor_(self.upper_bound, im1)
obj2 = self._interval_metadata_constructor_(self.upper_bound)
obj2.interval_metadata.add(**self.intvls[0])
self.assertReallyEqual(obj1, obj2)
def test_raise_subregion(self):
im = IntervalMetadata(None)
im.add([(0, 3), (7, 9)], metadata={'type': 'gene'})
with io.StringIO() as fh:
with self.assertRaises(GFF3FormatError):
_serialize_interval_metadata(im,
seq_id='a',
fh=fh,
skip_subregion=False)
def test_eq_basic(self):
im1 = IntervalMetadata(self.upper_bound)
im1.add(**self.intvls[0])
obj1 = self._interval_metadata_constructor_(self.upper_bound, im1)
im2 = IntervalMetadata(self.upper_bound)
im2.add(**self.intvls[0])
obj2 = self._interval_metadata_constructor_(self.upper_bound, im2)
self.assertReallyEqual(obj1, obj2)
def test_init_copy_from(self):
for i in [None, 99, 999]:
obs = IntervalMetadata(i, self.im_1)
exp = IntervalMetadata(i)
exp.add(bounds=[(1, 2), (4, self.upper_bound)],
metadata={
'gene': 'sagA',
'bound': 0
})
self.assertEqual(obs, exp)
def test_transcribe_preserves_all_metadata(self):
im = IntervalMetadata(4)
im.add([(0, 2)], metadata={'gene': 'p53'})
exp = RNA('AGUU', metadata={'foo': 'bar'},
positional_metadata={'foo': range(4)},
interval_metadata=im)
seq = DNA('AGTT', metadata={'foo': 'bar'},
positional_metadata={'foo': range(4)},
interval_metadata=im)
self.assertEqual(seq.transcribe(), exp)
def test_upper_bound_is_none(self):
im = IntervalMetadata(None)
# should not raise error
im.add([(0, 1000000000)])
self.assertIsNone(im.upper_bound)
with self.assertRaisesRegex(
TypeError, r'upper bound is `None`'):
im._reverse()
with self.assertRaisesRegex(
TypeError, r'upper bound is `None`'):
IntervalMetadata.concat([self.im_1, im])
def test_interval_metadata_to_gff3_missing_field(self):
exp = 'ctg123\t.\tgene\t1\t9\t.\t.\t.\tID=gene00001;Name=EDEN'
imd = IntervalMetadata(9)
imd.add([(0, 9)], metadata={
'type': 'gene', 'ID': 'gene00001', 'Name': 'EDEN'})
with io.StringIO() as fh:
_interval_metadata_to_gff3(imd, fh, seq_id='ctg123')
# only compare the uncommented lines because the comments are not
# stored in IntervalMetadata
obs = [i for i in fh.getvalue().splitlines()
if not i.startswith('#')]
self.assertEqual([exp], obs)
def test_interval_metadata_to_gff3_multiple_values(self):
# test multiple values of db_xref are correctly serialized
exp = 'ctg123\t.\tgene\t1\t9\t.\t.\t.\tDbxref=GO:000152,GO:001234'
imd = IntervalMetadata(9)
imd.add([(0, 9)], metadata={
'type': 'gene', 'db_xref': ['GO:000152', 'GO:001234']})
with io.StringIO() as fh:
_interval_metadata_to_gff3(imd, fh, seq_id='ctg123')
# only compare the uncommented lines because the comments are not
# stored in IntervalMetadata
obs = [i for i in fh.getvalue().splitlines()
if not i.startswith('#')]
self.assertEqual([exp], obs)
def test_init_nondefault_parameters(self):
im = IntervalMetadata(8)
im.add([(1, 8)], metadata={'gene': 'p53'})
seq = ExampleGrammaredSequence(
'.-ABCXYZ',
metadata={'id': 'foo'},
positional_metadata={'quality': range(8)},
interval_metadata=im)
npt.assert_equal(seq.values, np.array('.-ABCXYZ', dtype='c'))
self.assertEqual(seq.metadata, {'id': 'foo'})
assert_data_frame_almost_equal(seq.positional_metadata,
pd.DataFrame({'quality': range(8)}))
self.assertEqual(seq.interval_metadata, im)
def test_init_nondefault_parameters(self):
im = IntervalMetadata(8)
im.add([(1, 8)], metadata={'gene': 'p53'})
seq = ExampleGrammaredSequence(
'.-ABCXYZ',
metadata={'id': 'foo'},
positional_metadata={'quality': range(8)},
interval_metadata=im)
npt.assert_equal(seq.values, np.array('.-ABCXYZ', dtype='c'))
self.assertEqual(seq.metadata, {'id': 'foo'})
assert_data_frame_almost_equal(seq.positional_metadata,
pd.DataFrame({'quality': range(8)}))
self.assertEqual(seq.interval_metadata, im)
def test_interval_metadata_to_gff3_escape(self):
# test escape of reserved char in GFF3
exp = 'ctg123\t.\tgene\t1\t9\t.\t.\t.\tID=a%3B%3D%26%2Cb'
imd = IntervalMetadata(9)
imd.add([(0, 9)], metadata={
'type': 'gene', 'ID': 'a;=&,b'})
with io.StringIO() as fh:
_interval_metadata_to_gff3(imd, fh, seq_id='ctg123')
# only compare the uncommented lines because the comments are not
# stored in IntervalMetadata
obs = [i for i in fh.getvalue().splitlines()
if not i.startswith('#')]
self.assertEqual([exp], obs)
def test_interval_metadata_to_gff3_escape(self):
# test escape of reserved char in GFF3
exp = 'ctg123\t.\tgene\t1\t9\t.\t.\t.\tID=a%3B%3D%26%2Cb'
imd = IntervalMetadata(9)
imd.add([(0, 9)], metadata={'type': 'gene', 'ID': 'a;=&,b'})
with io.StringIO() as fh:
_interval_metadata_to_gff3(imd, fh, seq_id='ctg123')
# only compare the uncommented lines because the comments are not
# stored in IntervalMetadata
obs = [
i for i in fh.getvalue().splitlines() if not i.startswith('#')
]
self.assertEqual([exp], obs)
def test_parse(self):
fp = get_data_path('transtermhp.tt')
exps = [('gi|556503834|ref|NC_000913.3|1', 12),
('gi|556503834|ref|NC_000913.3|2', 4)]
for (sid, imd), exp in zip(_generator(fp), exps):
self.assertEqual(sid, exp[0])
self.assertEqual(imd.num_interval_features, exp[1])
# test the interval metadata from the 2nd sequence
exp_imd = IntervalMetadata(None)
exp_imd.add(
[(7857, 7876)],
metadata={
'strand': '+',
'confidence': '95',
'sequence':
'TGCCCACGATTAAAG/GTGGCCGC/CCTG/GCGGTCAC/TTCTTTGAGAAAAGG',
'source': 'TransTermHP',
'ID': 'TERM_1',
'gene_id': '2_7',
'type': 'terminator'
})
exp_imd.add(
[(8919, 8958)],
metadata={
'strand': '-',
'confidence': '100',
'sequence':
'AATGAGCCAGAATAA/GCTAAGGTTGAAGGGGC/TGGAAC/GCCCCTTCAACCTTAGC/AGTAGCGTGGGATGA',
'source': 'TransTermHP',
'ID': 'TERM_2',
'gene_id': '2_9',
'type': 'terminator'
})
exp_imd.add(
[(9258, 9273)],
metadata={
'strand': '+',
'confidence': '89',
'sequence':
'GGCAGAAACAAAAAA/TCCCCG/GACT/CGGGGA/TTTATGTACAAGAGG',
'ID': 'TERM_3',
'gene_id': '2_9',
'source': 'TransTermHP',
'type': 'terminator'
})
exp_imd.add(
[(9258, 9273)],
metadata={
'strand': '-',
'confidence': '100',
'sequence':
'GGCAGAAACAAAAAA/TCCCCG/GACT/CGGGGA/TTTATGTACAAGAGG',
'ID': 'TERM_4',
'gene_id': '2_9',
'source': 'TransTermHP',
'type': 'terminator'
})
self.assertEqual(exp_imd, imd)
def test_interval_metadata_to_gff3_missing_field(self):
exp = 'ctg123\t.\tgene\t1\t9\t.\t.\t.\tID=gene00001;Name=EDEN'
imd = IntervalMetadata(9)
imd.add([(0, 9)],
metadata={
'type': 'gene',
'ID': 'gene00001',
'Name': 'EDEN'
})
with io.StringIO() as fh:
_interval_metadata_to_gff3(imd, fh, seq_id='ctg123')
# only compare the uncommented lines because the comments are not
# stored in IntervalMetadata
obs = [
i for i in fh.getvalue().splitlines() if not i.startswith('#')
]
self.assertEqual([exp], obs)
def test_interval_metadata_to_gff3_multiple_values(self):
# test multiple values of db_xref are correctly serialized
exp = 'ctg123\t.\tgene\t1\t9\t.\t.\t.\tDbxref=GO:000152,GO:001234'
imd = IntervalMetadata(9)
imd.add([(0, 9)],
metadata={
'type': 'gene',
'db_xref': ['GO:000152', 'GO:001234']
})
with io.StringIO() as fh:
_interval_metadata_to_gff3(imd, fh, seq_id='ctg123')
# only compare the uncommented lines because the comments are not
# stored in IntervalMetadata
obs = [
i for i in fh.getvalue().splitlines() if not i.startswith('#')
]
self.assertEqual([exp], obs)
def test_filter_partial_genes(self):
in_fp = join(self.tmpd, 'in.gff')
out_fp = join(self.tmpd, 'out.gff')
imd1 = IntervalMetadata(None)
imd1.add(
[(0, 100)],
metadata={
'partial': '01',
'phase': 0,
'source': 'Prodigal_v2.6.3',
'strand': '.',
'type': '.',
'score': '.'
})
imd2 = IntervalMetadata(None)
imd2.add(
[(200, 300)],
metadata={
'partial': '10',
'phase': 1,
'source': 'Prodigal_v2.6.3',
'strand': '-',
'type': 'CDS',
'score': '1'
})
imd2.add(
[(2000, 3000)],
metadata={
'partial': '00',
'phase': 1,
'source': 'Prodigal_v2.6.3',
'strand': '.',
'type': '.',
'score': '.'
})
imd3 = IntervalMetadata(None)
imd3.add(
[(2000, 3000)],
metadata={
'partial': '00',
'phase': 1,
'source': 'Prodigal_v2.6.3',
'strand': '.',
'type': '.',
'score': '.'
})
data = (('seq1', imd1), ('seq2', imd2))
write(((sid, imd) for sid, imd in data), into=in_fp, format='gff3')
filter_partial_genes(in_fp, out_fp)
obs = read(out_fp, format='gff3')
for i, j in zip(obs, [('seq2', imd3)]):
self.assertEqual(i, j)
def test_complement_without_reverse_non_empty(self):
for (constructor, seq_str, comp_str,
qual) in self.all_combos_comp_qual:
comp = constructor(seq_str).complement()
self.assertEqual(comp, constructor(comp_str))
im = IntervalMetadata(len(seq_str))
im.add([(0, 1)], metadata={'gene': 'p53'})
comp = constructor(
seq_str,
metadata={'id': 'foo', 'description': 'bar'},
positional_metadata={'quality': qual},
interval_metadata=im).complement()
self.assertEqual(
comp,
constructor(
comp_str,
metadata={'id': 'foo', 'description': 'bar'},
positional_metadata={'quality': qual},
interval_metadata=im))
def test_parse(self):
imd1 = IntervalMetadata(None)
imd1.add(bounds=[(237929, 238006)],
metadata={
'strand': '+',
'type': 'tRNA',
'source': 'Aragorn',
'product': 'tRNA-Ile'
})
imd1.add(bounds=[(238048, 238124)],
metadata={
'strand': '+',
'type': 'tRNA',
'source': 'Aragorn',
'product': 'tRNA-Ala'
})
imd2 = IntervalMetadata(None)
imd2.add(bounds=[(4954141, 4954228)],
metadata={
'strand': '-',
'type': 'tRNA',
'source': 'Aragorn',
'product': 'tRNA-Ser'
})
imd3 = IntervalMetadata(None)
exp = (('NC_016822.1', imd1), ('NC_016833.1', imd2), ('NC_016834.1',
imd3))
fp = get_data_path('aragorn.txt')
gen = _generator(fp)
for (exp_id, exp_imd), (obs_id, obs_imd) in zip(exp, gen):
self.assertEqual(exp_id, obs_id)
self.assertEqual(exp_imd, obs_imd)
def test_parse(self):
imd1 = IntervalMetadata(None)
imd1.add(bounds=[(252151, 252184)],
metadata={
'source': 'Tandem_Repeats_Finder',
'repeat': 'T',
'type': 'tandem_repeat'
})
imd1.add(bounds=[(261169, 261210)],
metadata={
'source': 'Tandem_Repeats_Finder',
'repeat': 'CTCTGA',
'type': 'tandem_repeat'
})
imd2 = IntervalMetadata(None)
imd2.add(bounds=[(172614, 172703)],
metadata={
'source': 'Tandem_Repeats_Finder',
'repeat': 'AACAGCCGC',
'type': 'tandem_repeat'
})
exp = (('NC_016822.1', imd1), ('NC_016833.1', imd2))
fp = get_data_path('tandem_repeats_finder.txt')
gen = _generator(fp)
for (exp_id, exp_imd), (obs_id, obs_imd) in zip(exp, gen):
self.assertEqual(exp_id, obs_id)
self.assertEqual(exp_imd, obs_imd)
def test_parse(self):
imd1 = IntervalMetadata(None)
imd1.add(bounds=[(3588441, 3588818)],
metadata={
'ncRNA_class': 'RNaseP_bact_a',
'type': 'ncRNA',
'strand': '-',
'db_xref': 'RF00010',
'source': 'Rfam'
})
imd1.add(bounds=[(3355449, 3355633)],
metadata={
'ncRNA_class': '5S_rRNA',
'type': 'rRNA',
'strand': '+',
'product': '5s_rRNA',
'db_xref': 'RF00001',
'source': 'Rfam'
})
imd2 = IntervalMetadata(None)
imd2.add(bounds=[(85215, 85384)],
metadata={
'ncRNA_class': 'LSU_rRNA_bacteria',
'type': 'rRNA',
'strand': '+',
'product': '23s_rRNA',
'db_xref': 'RF02541',
'source': 'Rfam'
})
imd3 = IntervalMetadata(None)
imd3.add(bounds=[(8739, 8777)],
metadata={
'ncRNA_class': 'SSU_rRNA_bacteria',
'type': 'rRNA',
'strand': '+',
'product': '16s_rRNA',
'db_xref': 'RF00177',
'source': 'Rfam'
})
exp = (('NC_016822.1', imd1), ('NC_016833.1', imd2), ('NC_016834.1',
imd3))
fp = get_data_path('cmscan.txt')
gen = _generator(fp)
for (exp_id, exp_imd), (obs_id, obs_imd) in zip(exp, gen):
self.assertEqual(exp_id, obs_id)
self.assertEqual(exp_imd, obs_imd)
def test_serialize_location(self):
imd = IntervalMetadata(9)
i1 = imd.add([(0, 1)])
self.assertEqual(_serialize_location(i1), '1')
i2 = imd.add([(0, 2)], [(True, True)])
self.assertEqual(_serialize_location(i2), '<1..>2')
i3 = imd.add([(0, 2)], [(False, True)])
self.assertEqual(_serialize_location(i3), '1..>2')
i4 = imd.add([(0, 2)], [(True, False)])
self.assertEqual(_serialize_location(i4), '<1..2')
i5 = imd.add([(0, 2), (3, 9)], metadata={'strand': '-'})
self.assertEqual(_serialize_location(i5),
'complement(join(1..2,4..9))')
i6 = imd.add([(0, 2), (3, 9)], [(True, False), (False, True)],
metadata={'strand': '-'})
self.assertEqual(_serialize_location(i6),
'complement(join(<1..2,4..>9))')
def test_serialize_location(self):
imd = IntervalMetadata(9)
i1 = imd.add([(0, 1)])
self.assertEqual(_serialize_location(i1), '1')
i2 = imd.add([(0, 2)], [(True, True)])
self.assertEqual(_serialize_location(i2), '<1..>2')
i3 = imd.add([(0, 2)], [(False, True)])
self.assertEqual(_serialize_location(i3), '1..>2')
i4 = imd.add([(0, 2)], [(True, False)])
self.assertEqual(_serialize_location(i4), '<1..2')
i5 = imd.add([(0, 2), (3, 9)], metadata={'strand': '-'})
self.assertEqual(_serialize_location(i5),
'complement(join(1..2,4..9))')
i6 = imd.add([(0, 2), (3, 9)],
[(True, False), (False, True)],
metadata={'strand': '-'})
self.assertEqual(_serialize_location(i6),
'complement(join(<1..2,4..>9))')
def test_parse(self):
imd1 = IntervalMetadata(None)
imd1.add(bounds=[(0, 2853)],
metadata={
'source': 'RNAmmer-1.2',
'type': 'rRNA',
'product': '23s_rRNA',
'strand': '-',
'score': '3222.8'
})
imd1.add(bounds=[(2924, 3040)],
metadata={
'source': 'RNAmmer-1.2',
'type': 'rRNA',
'product': '5s_rRNA',
'strand': '+',
'score': '80.8'
})
imd2 = IntervalMetadata(None)
imd2.add(bounds=[(77272, 78834)],
metadata={
'source': 'RNAmmer-1.2',
'type': 'rRNA',
'product': '16s_rRNA',
'strand': '+',
'score': '1984.2'
})
exp = (('NZ_JXDA01000005.1', imd1), ('NZ_JXDA01000001.1', imd2))
fp = get_data_path('rnammer.gff')
gen = _generator(fp)
for (exp_id, exp_imd), (obs_id, obs_imd) in zip(exp, gen):
self.assertEqual(exp_id, obs_id)
self.assertEqual(exp_imd, obs_imd)
class GFF3IOTests(TestCase):
def setUp(self):
self.multi_fp = get_data_path('gff3_multi_record')
self.single_fp = get_data_path('gff3_single_record')
intvls = [{'bounds': [(0, 4641652)],
'metadata': {'source': 'European Nucleotide Archive',
'type': 'chromosome',
'score': '.',
'strand': '.',
'ID': 'chromosome:Chromosome',
'Alias': 'U00096.3',
'Is_circular': 'true'}},
{'bounds': [(147, 148)],
'metadata': {'source': 'regulondb_feature',
'type': 'biological_region',
'score': '.',
'strand': '+',
'external_name':
'Promoter thrLp (RegulonDB:ECK120010236)',
'logic_name': 'regulondb_promoter'}},
{'bounds': [(336, 2799)],
'metadata': {'source': 'Prodigal_v2.60',
'type': 'gene',
'score': '1.8',
'strand': '+',
'phase': 0,
'ID': '1_1',
'gc_cont': '0.427'}},
{'bounds': [(336, 2799)],
'metadata': {'source': 'Prodigal_v2.60',
'type': 'CDS',
'score': '333.8',
'strand': '+',
'phase': 0,
'ID': '1_2',
'Parent': '1_1',
'rbs_motif': 'GGAG/GAGG',
'rbs_spacer': '5-10bp'}},
{'bounds': [(0, 50), (55, 100)],
'metadata': {'source': 'Prodigal_v2.60',
'type': 'gene',
'score': '1.8',
'strand': '+',
'phase': 0,
'ID': '1_1',
'gene': 'FXR receptor'}}]
self.upper_bound = 4641652
self.imd1 = IntervalMetadata(self.upper_bound)
self.imd1.add(**intvls[0])
self.imd1.add(**intvls[1])
self.imd2 = IntervalMetadata(None)
self.imd2.add(**intvls[2])
self.imd2.add(**intvls[3])
self.imd3 = IntervalMetadata(None)
self.imd3.add(**intvls[4])
self.seq_fp = get_data_path('gff3_dna')
self.seq = Sequence('ATGCATGCATGC',
metadata={'id': 'NC_1',
'description': 'species X'})
self.seq.interval_metadata.add(
[(0, 9)],
metadata={'source': 'Prodigal_v2.60',
'type': 'gene',
'score': '.',
'strand': '+',
'phase': 0,
'ID': 'gene1',
'Name': 'FXR'})
self.dna = DNA(self.seq)
def test_eq_ne(self):
im1 = IntervalMetadata(10)
im1.add(metadata={'gene': 'sagA', 'bound': '0'},
bounds=[(0, 2), (4, 7)])
im1.add(metadata={'gene': 'sagB', 'bound': '3'},
bounds=[(3, 5)])
# The ordering shouldn't matter
im2 = IntervalMetadata(10)
im2.add(metadata={'gene': 'sagB', 'bound': '3'},
bounds=[(3, 5)])
im2.add(metadata={'gene': 'sagA', 'bound': '0'},
bounds=[(0, 2), (4, 7)])
im3 = IntervalMetadata(10)
im3.add(metadata={'gene': 'sagA', 'bound': '3'},
bounds=[(0, 2), (4, 7)])
im3.add(metadata={'gene': 'sagB', 'bound': '3'},
bounds=[(3, 5)])
self.assertReallyEqual(im1, im2)
self.assertReallyNotEqual(im1, im3)
def test_compute_rrna_score(self):
imd1 = IntervalMetadata(None)
imd1.add([(0, 100)], metadata={'type': 'rRNA', 'product': '5s_rRNA'})
imd1.add([(0, 725)], metadata={'type': 'rRNA', 'product': '16s_rRNA'})
imd1.add([(0, 12)], metadata={'type': 'tRNA'})
imd2 = IntervalMetadata(None)
imd2.add([(0, 10)], metadata={'type': 'rRNA', 'product': '5s_rRNA'})
imd2.add([(0, 1450)], metadata={'type': 'rRNA', 'product': '16s_rRNA'})
imd3 = IntervalMetadata(None)
imd3.add([(0, 2900)], metadata={'type': 'rRNA', 'product': '23s_rRNA'})
obs = compute_rrna_score([imd1, imd2, imd3])
exp = 0.1 + sum([0.3] * 3)
self.assertEqual(obs, exp)
obs = compute_rrna_score([imd1, imd2])
exp = 0.1 + sum([0.3] * 2)
self.assertEqual(obs, exp)
obs = compute_rrna_score([])
self.assertEqual(obs, 0.1)
obs = compute_rrna_score([imd2])
self.assertEqual(obs, 0.5)
obs = compute_rrna_score([imd1])
self.assertEqual(obs, 0.6)
class TestIntervalMetadata(unittest.TestCase, ReallyEqualMixin):
def setUp(self):
self.upper_bound = 10
self.im_empty = IntervalMetadata(self.upper_bound)
self.im_1 = IntervalMetadata(self.upper_bound)
self.im_1_1 = Interval(
interval_metadata=self.im_1,
bounds=[(1, 2), (4, self.upper_bound)],
metadata={'gene': 'sagA', 'bound': 0})
self.im_2 = IntervalMetadata(self.upper_bound)
self.im_2_1 = Interval(
interval_metadata=self.im_2,
bounds=[(1, 2), (4, self.upper_bound)],
metadata={'gene': 'sagA', 'bound': 0})
self.im_2_2 = Interval(
interval_metadata=self.im_2,
bounds=[(3, 5)],
metadata={'gene': 'sagB', 'bound': 0, 'spam': [0]})
def test_copy_empty(self):
obs = copy(self.im_empty)
self.assertEqual(obs, self.im_empty)
self.assertIsNot(obs._intervals, self.im_empty._intervals)
self.assertIsNot(obs._interval_tree, self.im_empty._interval_tree)
def test_copy(self):
obs = copy(self.im_2)
self.assertEqual(obs, self.im_2)
self.assertIsNot(obs._intervals, self.im_2._intervals)
self.assertIsNot(obs._interval_tree, self.im_2._interval_tree)
for i in range(self.im_2.num_interval_features):
i1, i2 = obs._intervals[i], self.im_2._intervals[i]
self.assertIsNot(i1, i2)
self.assertIsNot(i1.bounds, i2.bounds)
self.assertIsNot(i1.fuzzy, i2.fuzzy)
self.assertIsNot(i1._interval_metadata, i2._interval_metadata)
self.assertIsNot(i1.metadata, i2.metadata)
for k in i1.metadata:
self.assertIs(i1.metadata[k], i2.metadata[k])
def test_deepcopy(self):
obs = deepcopy(self.im_2)
self.assertEqual(obs, self.im_2)
self.assertIsNot(obs._intervals, self.im_2._intervals)
self.assertIsNot(obs._interval_tree, self.im_2._interval_tree)
for i in range(self.im_2.num_interval_features):
i1, i2 = obs._intervals[i], self.im_2._intervals[i]
self.assertIsNot(i1, i2)
self.assertIsNot(i1.bounds, i2.bounds)
self.assertIsNot(i1.fuzzy, i2.fuzzy)
self.assertIsNot(i1.metadata, i2.metadata)
i2.metadata['spam'].append(1)
self.assertEqual(i2.metadata,
{'gene': 'sagB', 'bound': 0, 'spam': [0, 1]})
self.assertEqual(i1.metadata,
{'gene': 'sagB', 'bound': 0, 'spam': [0]})
def test_deepcopy_memo_is_respected(self):
memo = {}
deepcopy(self.im_1, memo)
self.assertGreater(len(memo), 2)
def test_init(self):
self.assertFalse(self.im_empty._is_stale_tree)
self.assertEqual(self.im_empty._intervals, [])
def test_init_upper_bound_lt_lower_bound(self):
# test that no exception is raised
IntervalMetadata(0)
with self.assertRaises(ValueError):
IntervalMetadata(-1)
def test_upper_bound_is_none(self):
im = IntervalMetadata(None)
# should not raise error
im.add([(0, 1000000000)])
self.assertIsNone(im.upper_bound)
with self.assertRaisesRegex(
TypeError, r'upper bound is `None`'):
im._reverse()
with self.assertRaisesRegex(
TypeError, r'upper bound is `None`'):
IntervalMetadata.concat([self.im_1, im])
def test_init_copy_from(self):
for i in [None, 99, 999]:
obs = IntervalMetadata(i, self.im_1)
exp = IntervalMetadata(i)
exp.add(bounds=[(1, 2), (4, self.upper_bound)],
metadata={'gene': 'sagA', 'bound': 0})
self.assertEqual(obs, exp)
def test_init_copy_from_empty(self):
for i in [None, 0, 9, 99, 999]:
obs = IntervalMetadata(i, self.im_empty)
exp = IntervalMetadata(i)
self.assertEqual(obs, exp)
# test it is shallow copy
self.assertIsNot(obs._intervals, self.im_empty._intervals)
self.assertIsNot(obs._interval_tree, self.im_empty._interval_tree)
def test_init_copy_from_shallow_copy(self):
obs = IntervalMetadata(self.upper_bound, self.im_2)
self.assertEqual(self.im_2, obs)
# test it is shallow copy
self.assertIsNot(obs._intervals, self.im_2._intervals)
self.assertIsNot(obs._interval_tree, self.im_2._interval_tree)
for i in range(self.im_2.num_interval_features):
i1, i2 = obs._intervals[i], self.im_2._intervals[i]
self.assertIsNot(i1, i2)
self.assertIsNot(i1.bounds, i2.bounds)
self.assertIsNot(i1.fuzzy, i2.fuzzy)
self.assertIsNot(i1._interval_metadata, i2._interval_metadata)
self.assertIsNot(i1.metadata, i2.metadata)
for k in i1.metadata:
self.assertIs(i1.metadata[k], i2.metadata[k])
def test_init_copy_from_error(self):
i = self.upper_bound - 1
with self.assertRaisesRegex(
ValueError, r'larger than upper bound \(%r\)' % i):
IntervalMetadata(i, self.im_2)
def test_num_interval_features(self):
self.assertEqual(self.im_empty.num_interval_features, 0)
self.assertEqual(self.im_1.num_interval_features, 1)
self.assertEqual(self.im_2.num_interval_features, 2)
def test_duplicate(self):
'''Test query and drop methods on duplicate Intervals.'''
intvl_1 = self.im_empty.add([(1, 2)])
intvl_2 = self.im_empty.add([(1, 2)])
self.assertEqual(len(list(self.im_empty.query([(1, 2)]))), 2)
self.im_empty.drop([intvl_1])
self.assertEqual(len(self.im_empty._intervals), 1)
self.assertTrue(self.im_empty._intervals[0] is intvl_2)
def test_duplicate_bounds(self):
intvl = self.im_empty.add([(1, 2), (1, 2)])
intvls = list(self.im_empty.query([(1, 2)]))
self.assertEqual(len(intvls), 1)
self.assertTrue(intvl is intvls[0])
def test_concat_empty(self):
for i in 0, 1, 2:
obs = IntervalMetadata.concat([self.im_empty] * i)
exp = IntervalMetadata(self.upper_bound * i)
self.assertEqual(obs, exp)
obs = IntervalMetadata.concat([])
self.assertEqual(obs, IntervalMetadata(0))
def test_concat(self):
im1 = IntervalMetadata(3)
im2 = IntervalMetadata(4)
im3 = IntervalMetadata(5)
im1.add([(0, 2)], [(True, True)])
im2.add([(0, 3)], [(True, False)], {'gene': 'sagA'})
im2.add([(2, 4)], metadata={'gene': 'sagB'})
im3.add([(1, 5)], [(False, True)], {'gene': 'sagC'})
obs = IntervalMetadata.concat([im1, im2, im3])
exp = IntervalMetadata(12)
exp.add(bounds=[(0, 2)], fuzzy=[(True, True)])
exp.add(bounds=[(3, 6)], fuzzy=[(True, False)],
metadata={'gene': 'sagA'})
exp.add(bounds=[(5, 7)], metadata={'gene': 'sagB'})
exp.add(bounds=[(8, 12)], fuzzy=[(False, True)],
metadata={'gene': 'sagC'})
self.assertEqual(obs, exp)
def test_merge(self):
# empty + empty
im = IntervalMetadata(self.upper_bound)
self.im_empty.merge(im)
self.assertEqual(self.im_empty, im)
# empty + non-empty
self.im_empty.merge(self.im_1)
self.assertEqual(self.im_empty, self.im_1)
# non-empty + non-empty
self.im_empty.merge(self.im_2)
self.im_2.merge(self.im_1)
self.assertEqual(self.im_empty, self.im_2)
def test_merge_unequal_upper_bounds(self):
n = 3
im1 = IntervalMetadata(n)
for im in [self.im_empty, self.im_1]:
with self.assertRaisesRegex(
ValueError,
r'not equal \(%d != %d\)' % (self.upper_bound, n)):
im.merge(im1)
def test_merge_to_unbounded(self):
for im in [self.im_empty, self.im_1, IntervalMetadata(None)]:
obs = IntervalMetadata(None)
obs.merge(im)
self.assertIsNone(obs.upper_bound)
self.assertEqual(obs._intervals, im._intervals)
def test_merge_unbounded_to_bounded(self):
im = IntervalMetadata(None)
with self.assertRaisesRegex(
ValueError,
r'Cannot merge an unbound IntervalMetadata object '
'to a bounded one'):
self.im_1.merge(im)
# original im is not changed
self.assertIsNone(im.upper_bound)
self.assertEqual(im._intervals, [])
def test_sort(self):
interval = Interval(
self.im_2,
[(1, 2), (3, 8)],
metadata={'gene': 'sagA', 'bound': 0})
im = deepcopy(self.im_2)
self.im_2.sort(False)
# check sorting does not have other side effects
self.assertEqual(im, self.im_2)
self.assertEqual(self.im_2._intervals,
[self.im_2_2, self.im_2_1, interval])
self.im_2.sort()
self.assertEqual(im, self.im_2)
self.assertEqual(self.im_2._intervals,
[interval, self.im_2_1, self.im_2_2])
self.im_empty.sort()
self.assertEqual(self.im_empty, IntervalMetadata(self.upper_bound))
def test_add_eq_upper_bound(self):
self.im_empty.add(bounds=[(1, 2), (4, self.upper_bound)],
metadata={'gene': 'sagA', 'bound': 0})
self.assertTrue(self.im_empty._is_stale_tree)
interval = self.im_empty._intervals[0]
self.assertEqual(interval.bounds, [(1, 2), (4, self.upper_bound)])
self.assertEqual(interval.metadata, {'gene': 'sagA', 'bound': 0})
self.assertTrue(isinstance(self.im_empty._interval_tree, IntervalTree))
def test_add_gt_upper_bound(self):
with self.assertRaises(ValueError):
self.im_empty.add(bounds=[(1, 2), (4, self.upper_bound+1)],
metadata={'gene': 'sagA', 'bound': 0})
def test_add_eq_start_end_bound(self):
for i in 0, 1, self.upper_bound:
# test that no exception is raised
self.im_empty.add(bounds=[(i, i)],
metadata={'gene': 'sagA', 'bound': 0})
def test_query_attribute(self):
intervals = self.im_2._query_attribute({})
for i, j in zip(intervals, self.im_2._intervals):
self.assertEqual(i, j)
intervals = list(self.im_2._query_attribute(None))
self.assertEqual(len(intervals), 0)
for i in self.im_2._intervals:
intervals = list(self.im_2._query_attribute(i.metadata))
self.assertEqual(len(intervals), 1)
self.assertEqual(intervals[0], i)
def test_query_interval(self):
intervals = list(self.im_2._query_interval((1, 2)))
self.assertEqual(len(intervals), 1)
self.assertEqual(intervals[0], self.im_2_1)
intervals = list(self.im_2._query_interval((3, 4)))
self.assertEqual(len(intervals), 1)
self.assertEqual(intervals[0], self.im_2_2)
intervals = {repr(i) for i in self.im_2._query_interval((1, 7))}
self.assertEqual(len(intervals), 2)
self.assertSetEqual(intervals,
{repr(i) for i in self.im_2._intervals})
def test_query_interval_upper_bound(self):
intervals = list(self.im_2._query_interval((self.upper_bound-1,
self.upper_bound)))
self.assertEqual(intervals, [self.im_2_1])
def test_query(self):
intervals = list(self.im_2.query(bounds=[(1, 5)],
metadata={'gene': 'sagA'}))
self.assertEqual(len(intervals), 1)
self.assertEqual(intervals[0], self.im_2_1)
def test_query_empty(self):
intervals = list(self.im_1.query())
self.assertEqual(len(intervals), 0)
def test_query_no_hits(self):
intervals = list(self.im_2.query(bounds=[(self.upper_bound, 200)]))
self.assertEqual(len(intervals), 0)
intervals = list(self.im_2.query(metadata={'gene': 'sagC'}))
self.assertEqual(len(intervals), 0)
intervals = list(self.im_2.query(bounds=[(1, 2)],
metadata={'gene': 'sagC'}))
self.assertEqual(len(intervals), 0)
def test_query_interval_only(self):
for loc in [[(1, 7)],
[(1, 2), (3, 4)]]:
intervals = list(self.im_2.query(bounds=loc))
self.assertEqual(len(intervals), 2)
self.assertEqual(intervals[0], self.im_2_1)
self.assertEqual(intervals[1], self.im_2_2)
def test_query_metadata_only(self):
intervals = list(self.im_2.query(metadata={'gene': 'sagB'}))
self.assertEqual(len(intervals), 1)
self.assertEqual(intervals[0], self.im_2_2)
intervals = list(self.im_2.query(metadata={'bound': 0}))
self.assertEqual(len(intervals), 2)
self.assertEqual(intervals[0], self.im_2_1)
self.assertEqual(intervals[1], self.im_2_2)
def test_drop(self):
intvl = self.im_2._intervals[0]
self.im_2.drop([intvl])
self.assertEqual(len(self.im_2._intervals), 1)
self.assertEqual(self.im_2._intervals[0], self.im_2_2)
# test the intvl was set to dropped
self.assertTrue(intvl.dropped)
def test_drop_all(self):
self.im_2.drop(self.im_2._intervals)
self.assertEqual(self.im_2, self.im_empty)
def test_drop_negate(self):
intvl = self.im_2._intervals[0]
self.im_2.drop([intvl], negate=True)
self.assertEqual(len(self.im_2._intervals), 1)
self.assertEqual(self.im_2._intervals[0], intvl)
# test the dropped intvl was set to dropped
self.assertTrue(self.im_2_2.dropped)
def test_reverse(self):
self.im_2._reverse()
Interval(
interval_metadata=self.im_empty,
bounds=[(0, 6), (8, 9)],
metadata={'gene': 'sagA', 'bound': 0})
Interval(
interval_metadata=self.im_empty,
bounds=[(5, 7)],
metadata={'gene': 'sagB', 'bound': 0, 'spam': [0]})
self.assertEqual(self.im_2, self.im_empty)
def test_eq_ne(self):
im1 = IntervalMetadata(10)
im1.add(metadata={'gene': 'sagA', 'bound': '0'},
bounds=[(0, 2), (4, 7)])
im1.add(metadata={'gene': 'sagB', 'bound': '3'},
bounds=[(3, 5)])
# The ordering shouldn't matter
im2 = IntervalMetadata(10)
im2.add(metadata={'gene': 'sagB', 'bound': '3'},
bounds=[(3, 5)])
im2.add(metadata={'gene': 'sagA', 'bound': '0'},
bounds=[(0, 2), (4, 7)])
im3 = IntervalMetadata(10)
im3.add(metadata={'gene': 'sagA', 'bound': '3'},
bounds=[(0, 2), (4, 7)])
im3.add(metadata={'gene': 'sagB', 'bound': '3'},
bounds=[(3, 5)])
self.assertReallyEqual(im1, im2)
self.assertReallyNotEqual(im1, im3)
def test_ne_diff_bounds(self):
im1 = IntervalMetadata(10)
im2 = IntervalMetadata(9)
intvl = {'bounds': [(0, 1)], 'metadata': {'spam': 'foo'}}
im1.add(**intvl)
im2.add(**intvl)
self.assertReallyNotEqual(im1, im2)
def test_repr(self):
exp = '''0 interval features
-------------------'''
self.assertEqual(repr(self.im_empty), exp)
self.im_empty.add([(1, 2)], metadata={'gene': 'sagA'})
exp = ("1 interval feature\n"
"------------------\n"
r"Interval\(interval_metadata=<[0-9]+>, bounds=\[\(1, 2\)\], "
r"fuzzy=\[\(False, False\)\], metadata={'gene': 'sagA'}\)")
self.assertRegex(repr(self.im_empty), exp)
self.im_empty.add([(3, 4)], metadata={'gene': 'sagB'})
self.im_empty.add([(3, 4)], metadata={'gene': 'sagC'})
self.im_empty.add([(3, 4)], metadata={'gene': 'sagD'})
self.im_empty.add([(3, 4)], metadata={'gene': 'sagE'})
self.im_empty.add([(3, 4)], metadata={'gene': 'sagF'})
exp = ("6 interval features\n"
"-------------------\n"
r"Interval\(interval_metadata=<[0-9]+>, bounds=\[\(1, 2\)\], "
r"fuzzy=\[\(False, False\)\], metadata={'gene': 'sagA'}\)\n"
r"Interval\(interval_metadata=<[0-9]+>, bounds=\[\(3, 4\)\], "
r"fuzzy=\[\(False, False\)\], metadata={'gene': 'sagB'}\)\n"
r"...\n"
r"Interval\(interval_metadata=<[0-9]+>, bounds=\[\(3, 4\)\], "
r"fuzzy=\[\(False, False\)\], metadata={'gene': 'sagE'}\)\n"
r"Interval\(interval_metadata=<[0-9]+>, bounds=\[\(3, 4\)\], "
r"fuzzy=\[\(False, False\)\], metadata={'gene': 'sagF'}\)")
self.assertRegex(repr(self.im_empty), exp)
def setUp(self):
# to test ID line
self.id = (
# This is a derived record (non-coding, rRNA and spacer records)
# (feature level record:
# http://www.ebi.ac.uk/ena/browse/feature-level-products
# TODO: a Uniprot record?
([
'ID AB000684.1:1..275:rRNA; SV 1; linear; '
'genomic DNA; STD; ENV; 275 BP.'
], {
'division': 'ENV',
'mol_type': 'genomic DNA',
'shape': 'linear',
'locus_name': 'AB000684.1:1..275:rRNA',
'unit': 'bp',
'size': 275,
'version': 1,
'class': 'STD',
'date': None
}),
# A standard record
(['ID M14399; SV 1; linear; mRNA; STD; PRO; 63 BP.'], {
'division': 'PRO',
'mol_type': 'mRNA',
'shape': 'linear',
'locus_name': 'M14399',
'unit': 'bp',
'size': 63,
'version': 1,
'class': 'STD',
'date': None
}))
# define a single DNA record (with no interval metadata)
# M14399; SV 1; linear; mRNA; STD; PRO; 63 BP.
self.single = (
'gtgaaacaaagcactattgcactggctgtcttaccgttactgtttacccctgtgacaaaagcc',
{
'LOCUS': {
'locus_name': 'M14399',
'class': 'STD',
'division': 'PRO',
'mol_type': 'mRNA',
'shape': 'linear',
'size': 63,
'unit': 'bp',
'version': 1,
'date': None
}
}, None, DNA)
# define a single protein record (uniprot)
self.protein = (
'MAFSAEDVLKEYDRRRRMEALLLSLYYPNDRKLLDYKEWSPPRVQVECPKAPVEWNNPPSEKG'
'LIVGHFSGIKYKGEKAQASEVDVNKMCCWVSKFKDAMRRYQGIQTCKIPGKVLSDLDAKIKAY'
'NLTVEGVEGFVRYSRVTKQHVAAFLKELRHSKQYENVNLIHYILTDKRVDIQHLEKDLVKDFK'
'ALVESAHRMRQGHMINVKYILYQLLKKHGHGPDGPDILTVKTGSKGVLYDDSFRKIYTDLGWK'
'FTPL', {
'LOCUS': {
'locus_name': '001R_FRG3G',
'status': 'Reviewed',
'size': 256,
'unit': 'aa'
}
}, None, Protein)
# define a single DNA record uppercase (filepath)
self.single_upper_fp = get_data_path('embl_single_record_upper')
# define a single RNA record lower
self.single_lower_fp = get_data_path('embl_single_record_lower')
# define a single RNA record file path
self.single_rna_fp = get_data_path('embl_single_record')
# define a http://www.ebi.ac.uk/ena/browse/feature-level-products
self.feature_level_fp = get_data_path("embl_feature_level_record")
# define a interval metadata (see skbio.metadata.IntervalMetadata)
imd = IntervalMetadata(63)
# then add interval object to interval metadata. Add source
imd.add(
[(0, 63)], [(False, False)], {
'db_xref': '"taxon:562"',
'mol_type': '"mRNA"',
'organism': '"Escherichia coli"',
'type': 'source',
'strand': '+',
'__location': '1..63'
})
imd.add(
[(0, 63)],
# the second True is beacause exact location is not known
[(False, True)],
{
'phase':
0,
'db_xref': [
'"GOA:P00634"', '"InterPro:IPR001952"',
'"InterPro:IPR017849"', '"InterPro:IPR017850"',
'"InterPro:IPR018299"', '"PDB:1AJA"', '"PDB:1AJB"',
'"PDB:1AJC"', '"PDB:1AJD"', '"PDB:1ALH"', '"PDB:1ALI"',
'"PDB:1ALJ"', '"PDB:1ALK"', '"PDB:1ANI"', '"PDB:1ANJ"',
'"PDB:1B8J"', '"PDB:1ED8"', '"PDB:1ED9"', '"PDB:1ELX"',
'"PDB:1ELY"', '"PDB:1ELZ"', '"PDB:1EW8"', '"PDB:1EW9"',
'"PDB:1HJK"', '"PDB:1HQA"', '"PDB:1KH4"', '"PDB:1KH5"',
'"PDB:1KH7"', '"PDB:1KH9"', '"PDB:1KHJ"', '"PDB:1KHK"',
'"PDB:1KHL"', '"PDB:1KHN"', '"PDB:1URA"', '"PDB:1URB"',
'"PDB:1Y6V"', '"PDB:1Y7A"', '"PDB:2ANH"', '"PDB:2G9Y"',
'"PDB:2GA3"', '"PDB:2MLX"', '"PDB:2MLY"', '"PDB:2MLZ"',
'"PDB:3BDF"', '"PDB:3BDG"', '"PDB:3BDH"', '"PDB:3CMR"',
'"PDB:3DPC"', '"PDB:3DYC"', '"PDB:3TG0"', '"PDB:4KM4"',
'"PDB:4YR1"', '"PDB:5C66"', '"PDB:5GAD"', '"PDB:5GAF"',
'"PDB:5GAG"', '"PDB:5GAH"', '"PDB:5JTL"', '"PDB:5JTM"',
'"PDB:5JTN"', '"PDB:5JTO"', '"PDB:5JTP"',
'"UniProtKB/Swiss-Prot:P00634"'
],
'__location':
'1..>63',
'strand':
'+',
'note':
'"alkaline phosphatase signal peptide"',
'protein_id':
'"AAA23431.1"',
'transl_table':
'11',
'translation':
'"MKQSTIALAVLPLLFTPVTKA"',
'type':
'CDS'
})
self.single_rna = (
'gugaaacaaagcacuauugcacuggcugucuuaccguuacuguuuaccccugugacaaaagcc',
{
'LOCUS': {
'locus_name': 'M14399',
'class': 'STD',
'division': 'PRO',
'mol_type': 'mRNA',
'shape': 'linear',
'size': 63,
'unit': 'bp',
'version': 1,
'date': '02-SEP-1999'
},
'ACCESSION':
'M14399;', # accessions (could be more than one)
'VERSION':
'M14399.1', # a genbank like version
'DATE': [
"16-JUL-1988 (Rel. 16, Created)",
"02-SEP-1999 (Rel. 60, Last updated, Version 3)"
],
'DBSOURCE':
'MD5; c9b40131b8622946b5aafdf5473b3d43.',
'DEFINITION':
"E.coli alkaline phosphatase signal mRNA, 5' end.",
'KEYWORDS':
"alkaline phosphatase; signal peptide.",
'SOURCE': {
"ORGANISM":
"Escherichia coli",
'taxonomy':
"Bacteria; Proteobacteria; "
"Gammaproteobacteria; Enterobacterales; "
"Enterobacteriaceae; Escherichia."
},
'REFERENCE': [{
'AUTHORS':
'Gray G.L., Baldridge J.S., '
'McKeown K.S., Heyneker H.L., '
'Chang C.N.;',
'JOURNAL':
'Gene 39(2-3):247-254(1985).',
'REFERENCE':
'1 (bases 1 to 63)',
'TITLE':
'"Periplasmic production of correctly '
'processed human growth hormone in '
'Escherichia coli: natural and bacterial '
'signal sequences are '
'interchangeable";',
'PUBMED':
'3912261'
}],
'CROSS_REFERENCE':
['DOI; 10.1016/0378-1119(85)'
'90319-1. PUBMED; 3912261.']
},
imd,
RNA)
# define a multi record. File path
self.multi_fp = get_data_path('embl_multi_records')
# define interval metadata (as single metadata)
imd1 = imd
# define interal metadata for multi 2
imd2 = IntervalMetadata(743)
# then add interval object to interval metadata. Add source
imd2.add(
[(0, 743)], [(False, False)], {
'organism': '"Ruditapes philippinarum"',
'type': 'source',
'__location': '1..743',
'strand': '+',
'mol_type': '"mRNA"',
'db_xref': '"taxon:129788"'
})
imd2.add(
[(57, 444)], [(False, False)], {
'translation':
'"MPGGKAGKDSGKAKAKAVSRSARAGLQFPVGRIHRHLKNRT'
'TSHG RVGATAAVYSAAILEYLTAEVLELAGNASKDLKVKRI'
'TPRHLQLAIRGDEELDSLIKAT IAGGGVIPHIHKSLIGKKG'
'GQQAK"',
'type':
'CDS',
'__location':
'58..444',
'protein_id':
'"APY18893.1"',
'strand':
'+',
'phase':
0,
'product':
'"histone"'
})
# multi object
self.multi = (
(
'GTGAAACAAAGCACTATTGCACTGGCTGTCTTACCGTTACTGTTTACCCCTGTGACAAAAGCC',
{
'LOCUS': {
'locus_name': 'M14399',
'class': 'STD',
'division': 'PRO',
'mol_type': 'mRNA',
'shape': 'linear',
'size': 63,
'unit': 'bp',
'version': 1,
'date': '02-SEP-1999'
},
'ACCESSION':
'M14399;', # accessions (could be more than one)
'VERSION':
'M14399.1', # a genbank like version
'DATE': [
"16-JUL-1988 (Rel. 16, Created)",
"02-SEP-1999 (Rel. 60, Last updated, Version 3)"
],
'DBSOURCE':
'MD5; c9b40131b8622946b5aafdf5473b3d43.',
'DEFINITION':
"E.coli alkaline phosphatase signal mRNA, 5' end.",
'KEYWORDS':
"alkaline phosphatase; signal peptide.",
'SOURCE': {
"ORGANISM":
"Escherichia coli",
'taxonomy':
"Bacteria; Proteobacteria; "
"Gammaproteobacteria; Enterobacterales; "
"Enterobacteriaceae; Escherichia."
},
'REFERENCE': [{
'AUTHORS':
'Gray G.L., Baldridge J.S., '
'McKeown K.S., Heyneker H.L., '
'Chang C.N.;',
'JOURNAL':
'Gene 39(2-3):247-254(1985).',
'REFERENCE':
'1 (bases 1 to 63)',
'TITLE':
'"Periplasmic production of correctly '
'processed human growth hormone in '
'Escherichia coli: natural and '
'bacterial signal sequences are '
'interchangeable";',
'PUBMED':
'3912261'
}],
'CROSS_REFERENCE':
['DOI; 10.1016/0378-1119(85)'
'90319-1. PUBMED; 3912261.']
},
imd1,
DNA),
('TGTGCACAGTCTACGCGTCATCTTGAAAGAAAGAACTACACTACTCCAAAAATAATCATGCC'
'TGGTGGAAAAGCTGGTAAAGATTCCGGAAAGGCCAAGGCTAAGGCAGTGTCAAGGTCCGCAA'
'GAGCTGGCTTACAGTTTCCAGTCGGACGTATTCACAGGCATTTGAAGAACAGAACCACTAGC'
'CACGGTCGTGTTGGAGCTACAGCAGCCGTTTACAGTGCAGCAATCCTTGAATACCTGACCGC'
'CGAAGTGCTTGAGTTGGCTGGAAACGCAAGTAAAGATCTCAAAGTAAAGAGAATCACCCCAC'
'GTCACTTGCAGTTGGCAATCAGAGGAGATGAAGAGTTGGATTCCCTAATTAAAGCCACAATC'
'GCTGGTGGTGGTGTTATTCCACATATCCACAAGTCACTTATTGGCAAGAAGGGAGGTCAGCA'
'AGCCAAATAAATTGGACATACTCATTCATCAGGGAACAATGTGTAGTGAATGTGTTAAAAAG'
'AACAATCTCATTGTGTAGCTCTTTAGTTTTATATGAATGTGTTAACATGGTCATTCACATCG'
'TATGACTCATAGAATCATCTGTGTATCATTTCATCCTCTCATTTTATAGCTCCTCATTTTCC'
'TTAGACTCATTAAAATTTTTATCTCGGAAAAATGTTTTTTCTACAATTTTAGCATTCATTTA'
'TCTTCATCTTGCTTTTATGTTTAATAAAACGAACTTATAATACCAAAAAAAAAAAAAAAAA', {
'ACCESSION':
'KX454487;',
'VERSION':
'KX454487.1',
'COMMENT':
'##Assembly-Data-START##\nSequencing Technology '
':: Sanger dideoxy sequencing\n##Assembly-Data-END##',
'DATE': [
'02-FEB-2017 (Rel. 131, Created)',
'02-FEB-2017 (Rel. 131, Last updated, Version 1)'
],
'DBSOURCE':
'MD5; cbc730cf7a8d694b50fb7dd6b993ae0d.',
'DEFINITION':
'Ruditapes philippinarum histone mRNA, '
'complete cds.',
'KEYWORDS':
'.',
'LOCUS': {
'locus_name': 'KX454487',
'class': 'STD',
'division': 'INV',
'mol_type': 'mRNA',
'shape': 'linear',
'size': 743,
'unit': 'bp',
'version': 1,
'date': '02-FEB-2017'
},
'REFERENCE': [{
'AUTHORS':
'Yang D., Zhao J., Wang Q.;',
'JOURNAL':
'Submitted (27-JUN-2016) to the INSDC. Key '
'Laboratory of Coastal Zone Environment Processes '
'and Ecological Remediation, Yantai Institute '
'of Coastal Zone Research (YIC), Chinese Academy '
'of Sciences (CAS), 17 Chunhui Road, Laishan '
'District, Yantai, Shandong 264003, China',
'REFERENCE':
'1 (bases 1 to 743)',
'TITLE':
';'
}],
'CROSS_REFERENCE': [None],
'SOURCE': {
'ORGANISM':
'Ruditapes philippinarum',
'taxonomy':
'Eukaryota; Metazoa; Lophotrochozoa; Mollusca; '
'Bivalvia; Heteroconchia; Euheterodonta; '
'Veneroida; Veneroidea; Veneridae; Ruditapes.'
}
}, imd2, DNA))
# define the feature level product obj
self.feature_level = (
'AAUUGAAGAGUUUGAUCAUGGCUCAGAUUGAACGCUGGCGGCAGGCCUAACACAUGCAAGUC'
'GAGCGGCAGCACAGAGGAACUUGUUCCUUGGGUGGCGAGCGGCGGACGGGUGAGUAAUGCCU'
'AGGAAAUUGCCCUGAUGUGGGGGAUAACCAUUGGAAACGAUGGCUAAUACCGCAUGAUGCCU'
'ACGGGCCAAAGAGGGGGACCUUCUGGCCUCUCGCGUCAGGAUAUGCCUAGGUGGGAUUAGCU'
'AGUUGGUGAGGUAAUGGCUCACCAAGGCGACGAUCCCUAGCUGGUCUGAGAGGAUGAUCAGC'
'CACACUGGAACUGAGACACGGUCCAGACUCCUACGGGAGGCAGCAGUGGGGAAUAUUGCACA'
'AUGGGCGCAAGCCUGAUGCAGCCAUGCCGCGUGUAUGAAGAAGGCCUUCGGGUUGUAAAGUA'
'CUUUCAGUCGUGAGGAAGGUGGUGUUGUUAAUAGCAGCAUCAUUUGACGUUAGCGACAGAAG'
'AAGCACCGGCUAACUCCGUGCCAGCAGCCGCGGUAAUACGGAGGGUGCGAGCGUUAAUCGGA'
'AUUACUGGGCGUAAAGCGCAUGCAGGUGGUGGAUUAAGUCAGAUGUGAAAGCCCGGGGCUCA'
'ACCUCGGAACCGCAUUUGAAACUGGUUCACUAGAGUACUGUAGAGGGGGGUAGAAUUUCAGG'
'UGUAGCGGUGAAAUGCGUAGAGAUCUGAAGGAAUACCGGUGGCGAAGGCGGCCCCCUGGACA'
'GAUACUGACACUCAGAUGCGAAAGCGUGGGGAGCAAACAGGAUUAGAUACCCUGGUAGUCCA'
'CGCCGUAAACGAUGUCUACUUGGAGGUUGUGGCCUUGAGCCGUGGCUUUCGGAGCUAACGCG'
'UUAAGUAGACCGCCUGGGGAGUACGGUCGCAAGAUUAAAACUCAAAUGAAUUGACGGGGGCC'
'CGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAUGCAACGCGAAGAACCUUACCUACUCUUG'
'ACAUCCAGAGAAGCCAGCGGAGACGCAGGUGUGCCUUCGGGAGCUCUGAGACAGGUGCUGCA'
'UGGCUGUCGUCAGCUCGUGUUGUGAAAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUUA'
'UCCUUGUUUGCCAGCGAGUCAUGUCGGGAACUCCAGGGAGACUGCCGGUGAUAAACCGGAGG'
'AAGGUGGGGACGACGUCAAGUCAUCAUGGCCCUUACGAGUAGGGCUACACACGUGCUACAAU'
'GGCGCAUACAGAGGGCAGCAAGCUAGCGAUAGUGAGCGAAUCCCAAAAAGUGCGUCGUAGUC'
'CGGAUUGGAGUCUGCAACUCGACUCCAUGAAGUCGGAAUCGCUAGUAAUCGUAGAUCAGAAU'
'GCUACGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCACACCAUGGGAGUGGGCUG'
'CAAAAGAAGUGGGUAGUUUAACCUUUCGGGGAGGACGCUCACCACUUUGUGGUUCAUGACUG'
'GGGUGAAGUCGUAACAAGGUAGCGCUAGGGGAACCUGGCGCUGGAUCACCUCCUUA', {
'DATE': [
'02-JUN-2014 (Rel. 121, Created)',
'04-FEB-2016 (Rel. 127, Last updated, Version 5)'
],
'DBSOURCE':
'SILVA-LSU; LK021130. SILVA-SSU; LK021130. MD5; '
'afd116bf2c1a13acbf40d63d82f0218c. BioSample; '
'SAMEA3865288.',
'DEFINITION':
'Vibrio anguillarum 16S rRNA',
'KEYWORDS':
'.',
'LOCUS': {
'locus_name': 'LK021130.1:74067..75610:rRNA',
'class': 'STD',
'division': 'PRO',
'mol_type': 'genomic DNA',
'shape': 'linear',
'size': 1544,
'unit': 'bp',
'version': 1,
'date': '04-FEB-2016'
},
'PARENT_ACCESSION':
'LK021130.1',
'VERSION':
'LK021130.1',
'PROJECT_IDENTIFIER':
'Project:PRJEB5701;',
'REFERENCE': [{
'AUTHORS':
'Holm K.;',
'JOURNAL':
'Submitted (26-MAR-2014) to the INSDC. '
'Norstruct, Dept of Chemistry, University of '
'Tromso, Science Park 3, NO-9037 Tromso, NORWAY.',
'TITLE':
';',
'REFERENCE':
'1'
}, {
'AUTHORS':
'Holm K.O., Nilsson K., Hjerde E., Willassen '
'N.P., Milton D.L.;',
'JOURNAL':
'Stand Genomic Sci. 10:60-60(2015).',
'TITLE':
'"Complete genome sequence of Vibrio anguillarum '
'strain NB10, a virulent isolate from the Gulf '
'of Bothnia";',
'REFERENCE':
'2',
'PUBMED':
'26380645'
}],
'CROSS_REFERENCE':
[None, 'DOI; 10.1186/s40793-015-0060-7. PUBMED; 26380645.'],
'SOURCE': {
'ORGANISM':
'Vibrio anguillarum',
'taxonomy':
'Bacteria; Proteobacteria; Gammaproteobacteria; '
'Vibrionales; Vibrionaceae; Vibrio.'
}
}, None, RNA)
# get the feature level file without FT
self.feature_level_fp = get_data_path(
"embl_feature_level_record_no_FT")
# get a genbank file in order to to file conversion
self.genbank_fp = get_data_path('genbank_single_record')
# a embl constructed sequence file path
self.embl_constructed_fp = get_data_path("embl_constructed")
# a simple embl version to perform embl->gb->embl conversion
self.single_rna_simple_fp = get_data_path("embl_single_record_simple")
def setUp(self):
# to test ID line
self.id = (
# This is a derived record (non-coding, rRNA and spacer records)
# (feature level record:
# http://www.ebi.ac.uk/ena/browse/feature-level-products
# TODO: a Uniprot record?
(['ID AB000684.1:1..275:rRNA; SV 1; linear; '
'genomic DNA; STD; ENV; 275 BP.'],
{'division': 'ENV', 'mol_type': 'genomic DNA', 'shape': 'linear',
'locus_name': 'AB000684.1:1..275:rRNA', 'unit': 'bp',
'size': 275, 'version': 1, 'class': 'STD', 'date': None}),
# A standard record
(['ID M14399; SV 1; linear; mRNA; STD; PRO; 63 BP.'],
{'division': 'PRO', 'mol_type': 'mRNA', 'shape': 'linear',
'locus_name': 'M14399', 'unit': 'bp',
'size': 63, 'version': 1, 'class': 'STD', 'date': None}))
# define a single DNA record (with no interval metadata)
# M14399; SV 1; linear; mRNA; STD; PRO; 63 BP.
self.single = (
'gtgaaacaaagcactattgcactggctgtcttaccgttactgtttacccctgtgacaaaagcc',
{'LOCUS': {'locus_name': 'M14399',
'class': 'STD',
'division': 'PRO',
'mol_type': 'mRNA',
'shape': 'linear',
'size': 63,
'unit': 'bp',
'version': 1,
'date': None}},
None,
DNA)
# define a single protein record (uniprot)
self.protein = (
'MAFSAEDVLKEYDRRRRMEALLLSLYYPNDRKLLDYKEWSPPRVQVECPKAPVEWNNPPSEKG'
'LIVGHFSGIKYKGEKAQASEVDVNKMCCWVSKFKDAMRRYQGIQTCKIPGKVLSDLDAKIKAY'
'NLTVEGVEGFVRYSRVTKQHVAAFLKELRHSKQYENVNLIHYILTDKRVDIQHLEKDLVKDFK'
'ALVESAHRMRQGHMINVKYILYQLLKKHGHGPDGPDILTVKTGSKGVLYDDSFRKIYTDLGWK'
'FTPL',
{'LOCUS': {'locus_name': '001R_FRG3G',
'status': 'Reviewed',
'size': 256,
'unit': 'aa'}},
None,
Protein)
# define a single DNA record uppercase (filepath)
self.single_upper_fp = get_data_path('embl_single_record_upper')
# define a single RNA record lower
self.single_lower_fp = get_data_path('embl_single_record_lower')
# define a single RNA record file path
self.single_rna_fp = get_data_path('embl_single_record')
# define a http://www.ebi.ac.uk/ena/browse/feature-level-products
self.feature_level_fp = get_data_path("embl_feature_level_record")
# define a interval metadata (see skbio.metadata.IntervalMetadata)
imd = IntervalMetadata(63)
# then add interval object to interval metadata. Add source
imd.add([(0, 63)],
[(False, False)],
{'db_xref': '"taxon:562"',
'mol_type': '"mRNA"',
'organism': '"Escherichia coli"',
'type': 'source',
'strand': '+',
'__location': '1..63'})
imd.add([(0, 63)],
# the second True is beacause exact location is not known
[(False, True)],
{'phase': 0,
'db_xref': ['"GOA:P00634"',
'"InterPro:IPR001952"',
'"InterPro:IPR017849"',
'"InterPro:IPR017850"',
'"InterPro:IPR018299"',
'"PDB:1AJA"',
'"PDB:1AJB"',
'"PDB:1AJC"',
'"PDB:1AJD"',
'"PDB:1ALH"',
'"PDB:1ALI"',
'"PDB:1ALJ"',
'"PDB:1ALK"',
'"PDB:1ANI"',
'"PDB:1ANJ"',
'"PDB:1B8J"',
'"PDB:1ED8"',
'"PDB:1ED9"',
'"PDB:1ELX"',
'"PDB:1ELY"',
'"PDB:1ELZ"',
'"PDB:1EW8"',
'"PDB:1EW9"',
'"PDB:1HJK"',
'"PDB:1HQA"',
'"PDB:1KH4"',
'"PDB:1KH5"',
'"PDB:1KH7"',
'"PDB:1KH9"',
'"PDB:1KHJ"',
'"PDB:1KHK"',
'"PDB:1KHL"',
'"PDB:1KHN"',
'"PDB:1URA"',
'"PDB:1URB"',
'"PDB:1Y6V"',
'"PDB:1Y7A"',
'"PDB:2ANH"',
'"PDB:2G9Y"',
'"PDB:2GA3"',
'"PDB:2MLX"',
'"PDB:2MLY"',
'"PDB:2MLZ"',
'"PDB:3BDF"',
'"PDB:3BDG"',
'"PDB:3BDH"',
'"PDB:3CMR"',
'"PDB:3DPC"',
'"PDB:3DYC"',
'"PDB:3TG0"',
'"PDB:4KM4"',
'"PDB:4YR1"',
'"PDB:5C66"',
'"PDB:5GAD"',
'"PDB:5GAF"',
'"PDB:5GAG"',
'"PDB:5GAH"',
'"PDB:5JTL"',
'"PDB:5JTM"',
'"PDB:5JTN"',
'"PDB:5JTO"',
'"PDB:5JTP"',
'"UniProtKB/Swiss-Prot:P00634"'],
'__location': '1..>63',
'strand': '+',
'note': '"alkaline phosphatase signal peptide"',
'protein_id': '"AAA23431.1"',
'transl_table': '11',
'translation': '"MKQSTIALAVLPLLFTPVTKA"',
'type': 'CDS'})
self.single_rna = (
'gugaaacaaagcacuauugcacuggcugucuuaccguuacuguuuaccccugugacaaaagcc',
{'LOCUS': {'locus_name': 'M14399',
'class': 'STD',
'division': 'PRO',
'mol_type': 'mRNA',
'shape': 'linear',
'size': 63,
'unit': 'bp',
'version': 1,
'date': '02-SEP-1999'},
'ACCESSION': 'M14399;', # accessions (could be more than one)
'VERSION': 'M14399.1', # a genbank like version
'DATE': ["16-JUL-1988 (Rel. 16, Created)",
"02-SEP-1999 (Rel. 60, Last updated, Version 3)"],
'DBSOURCE': 'MD5; c9b40131b8622946b5aafdf5473b3d43.',
'DEFINITION': "E.coli alkaline phosphatase signal mRNA, 5' end.",
'KEYWORDS': "alkaline phosphatase; signal peptide.",
'SOURCE': {"ORGANISM": "Escherichia coli",
'taxonomy': "Bacteria; Proteobacteria; "
"Gammaproteobacteria; Enterobacterales; "
"Enterobacteriaceae; Escherichia."},
'REFERENCE': [{'AUTHORS': 'Gray G.L., Baldridge J.S., '
'McKeown K.S., Heyneker H.L., '
'Chang C.N.;',
'JOURNAL': 'Gene 39(2-3):247-254(1985).',
'REFERENCE': '1 (bases 1 to 63)',
'TITLE': '"Periplasmic production of correctly '
'processed human growth hormone in '
'Escherichia coli: natural and bacterial '
'signal sequences are '
'interchangeable";',
'PUBMED': '3912261'}],
'CROSS_REFERENCE': ['DOI; 10.1016/0378-1119(85)'
'90319-1. PUBMED; 3912261.']},
imd,
RNA)
# define a multi record. File path
self.multi_fp = get_data_path('embl_multi_records')
# define interval metadata (as single metadata)
imd1 = imd
# define interal metadata for multi 2
imd2 = IntervalMetadata(743)
# then add interval object to interval metadata. Add source
imd2.add([(0, 743)],
[(False, False)],
{'organism': '"Ruditapes philippinarum"',
'type': 'source',
'__location': '1..743',
'strand': '+',
'mol_type': '"mRNA"',
'db_xref': '"taxon:129788"'})
imd2.add([(57, 444)],
[(False, False)],
{'translation': '"MPGGKAGKDSGKAKAKAVSRSARAGLQFPVGRIHRHLKNRT'
'TSHG RVGATAAVYSAAILEYLTAEVLELAGNASKDLKVKRI'
'TPRHLQLAIRGDEELDSLIKAT IAGGGVIPHIHKSLIGKKG'
'GQQAK"',
'type': 'CDS',
'__location': '58..444',
'protein_id': '"APY18893.1"',
'strand': '+',
'phase': 0,
'product': '"histone"'})
# multi object
self.multi = (
('GTGAAACAAAGCACTATTGCACTGGCTGTCTTACCGTTACTGTTTACCCCTGTGACAAAAGCC',
{'LOCUS': {'locus_name': 'M14399',
'class': 'STD',
'division': 'PRO',
'mol_type': 'mRNA',
'shape': 'linear',
'size': 63,
'unit': 'bp',
'version': 1,
'date': '02-SEP-1999'},
'ACCESSION': 'M14399;', # accessions (could be more than one)
'VERSION': 'M14399.1', # a genbank like version
'DATE': ["16-JUL-1988 (Rel. 16, Created)",
"02-SEP-1999 (Rel. 60, Last updated, Version 3)"],
'DBSOURCE': 'MD5; c9b40131b8622946b5aafdf5473b3d43.',
'DEFINITION': "E.coli alkaline phosphatase signal mRNA, 5' end.",
'KEYWORDS': "alkaline phosphatase; signal peptide.",
'SOURCE': {"ORGANISM": "Escherichia coli",
'taxonomy': "Bacteria; Proteobacteria; "
"Gammaproteobacteria; Enterobacterales; "
"Enterobacteriaceae; Escherichia."},
'REFERENCE': [{'AUTHORS': 'Gray G.L., Baldridge J.S., '
'McKeown K.S., Heyneker H.L., '
'Chang C.N.;',
'JOURNAL': 'Gene 39(2-3):247-254(1985).',
'REFERENCE': '1 (bases 1 to 63)',
'TITLE': '"Periplasmic production of correctly '
'processed human growth hormone in '
'Escherichia coli: natural and '
'bacterial signal sequences are '
'interchangeable";',
'PUBMED': '3912261'}],
'CROSS_REFERENCE': ['DOI; 10.1016/0378-1119(85)'
'90319-1. PUBMED; 3912261.']},
imd1,
DNA),
('TGTGCACAGTCTACGCGTCATCTTGAAAGAAAGAACTACACTACTCCAAAAATAATCATGCC'
'TGGTGGAAAAGCTGGTAAAGATTCCGGAAAGGCCAAGGCTAAGGCAGTGTCAAGGTCCGCAA'
'GAGCTGGCTTACAGTTTCCAGTCGGACGTATTCACAGGCATTTGAAGAACAGAACCACTAGC'
'CACGGTCGTGTTGGAGCTACAGCAGCCGTTTACAGTGCAGCAATCCTTGAATACCTGACCGC'
'CGAAGTGCTTGAGTTGGCTGGAAACGCAAGTAAAGATCTCAAAGTAAAGAGAATCACCCCAC'
'GTCACTTGCAGTTGGCAATCAGAGGAGATGAAGAGTTGGATTCCCTAATTAAAGCCACAATC'
'GCTGGTGGTGGTGTTATTCCACATATCCACAAGTCACTTATTGGCAAGAAGGGAGGTCAGCA'
'AGCCAAATAAATTGGACATACTCATTCATCAGGGAACAATGTGTAGTGAATGTGTTAAAAAG'
'AACAATCTCATTGTGTAGCTCTTTAGTTTTATATGAATGTGTTAACATGGTCATTCACATCG'
'TATGACTCATAGAATCATCTGTGTATCATTTCATCCTCTCATTTTATAGCTCCTCATTTTCC'
'TTAGACTCATTAAAATTTTTATCTCGGAAAAATGTTTTTTCTACAATTTTAGCATTCATTTA'
'TCTTCATCTTGCTTTTATGTTTAATAAAACGAACTTATAATACCAAAAAAAAAAAAAAAAA',
{'ACCESSION': 'KX454487;',
'VERSION': 'KX454487.1',
'COMMENT': '##Assembly-Data-START##\nSequencing Technology '
':: Sanger dideoxy sequencing\n##Assembly-Data-END##',
'DATE': ['02-FEB-2017 (Rel. 131, Created)',
'02-FEB-2017 (Rel. 131, Last updated, Version 1)'],
'DBSOURCE': 'MD5; cbc730cf7a8d694b50fb7dd6b993ae0d.',
'DEFINITION': 'Ruditapes philippinarum histone mRNA, '
'complete cds.',
'KEYWORDS': '.',
'LOCUS': {'locus_name': 'KX454487',
'class': 'STD',
'division': 'INV',
'mol_type': 'mRNA',
'shape': 'linear',
'size': 743,
'unit': 'bp',
'version': 1,
'date': '02-FEB-2017'},
'REFERENCE': [
{'AUTHORS': 'Yang D., Zhao J., Wang Q.;',
'JOURNAL': 'Submitted (27-JUN-2016) to the INSDC. Key '
'Laboratory of Coastal Zone Environment Processes '
'and Ecological Remediation, Yantai Institute '
'of Coastal Zone Research (YIC), Chinese Academy '
'of Sciences (CAS), 17 Chunhui Road, Laishan '
'District, Yantai, Shandong 264003, China',
'REFERENCE': '1 (bases 1 to 743)',
'TITLE': ';'}],
'CROSS_REFERENCE': [None],
'SOURCE': {
'ORGANISM': 'Ruditapes philippinarum',
'taxonomy': 'Eukaryota; Metazoa; Lophotrochozoa; Mollusca; '
'Bivalvia; Heteroconchia; Euheterodonta; '
'Veneroida; Veneroidea; Veneridae; Ruditapes.'}},
imd2,
DNA))
# define the feature level product obj
self.feature_level = (
'AAUUGAAGAGUUUGAUCAUGGCUCAGAUUGAACGCUGGCGGCAGGCCUAACACAUGCAAGUC'
'GAGCGGCAGCACAGAGGAACUUGUUCCUUGGGUGGCGAGCGGCGGACGGGUGAGUAAUGCCU'
'AGGAAAUUGCCCUGAUGUGGGGGAUAACCAUUGGAAACGAUGGCUAAUACCGCAUGAUGCCU'
'ACGGGCCAAAGAGGGGGACCUUCUGGCCUCUCGCGUCAGGAUAUGCCUAGGUGGGAUUAGCU'
'AGUUGGUGAGGUAAUGGCUCACCAAGGCGACGAUCCCUAGCUGGUCUGAGAGGAUGAUCAGC'
'CACACUGGAACUGAGACACGGUCCAGACUCCUACGGGAGGCAGCAGUGGGGAAUAUUGCACA'
'AUGGGCGCAAGCCUGAUGCAGCCAUGCCGCGUGUAUGAAGAAGGCCUUCGGGUUGUAAAGUA'
'CUUUCAGUCGUGAGGAAGGUGGUGUUGUUAAUAGCAGCAUCAUUUGACGUUAGCGACAGAAG'
'AAGCACCGGCUAACUCCGUGCCAGCAGCCGCGGUAAUACGGAGGGUGCGAGCGUUAAUCGGA'
'AUUACUGGGCGUAAAGCGCAUGCAGGUGGUGGAUUAAGUCAGAUGUGAAAGCCCGGGGCUCA'
'ACCUCGGAACCGCAUUUGAAACUGGUUCACUAGAGUACUGUAGAGGGGGGUAGAAUUUCAGG'
'UGUAGCGGUGAAAUGCGUAGAGAUCUGAAGGAAUACCGGUGGCGAAGGCGGCCCCCUGGACA'
'GAUACUGACACUCAGAUGCGAAAGCGUGGGGAGCAAACAGGAUUAGAUACCCUGGUAGUCCA'
'CGCCGUAAACGAUGUCUACUUGGAGGUUGUGGCCUUGAGCCGUGGCUUUCGGAGCUAACGCG'
'UUAAGUAGACCGCCUGGGGAGUACGGUCGCAAGAUUAAAACUCAAAUGAAUUGACGGGGGCC'
'CGCACAAGCGGUGGAGCAUGUGGUUUAAUUCGAUGCAACGCGAAGAACCUUACCUACUCUUG'
'ACAUCCAGAGAAGCCAGCGGAGACGCAGGUGUGCCUUCGGGAGCUCUGAGACAGGUGCUGCA'
'UGGCUGUCGUCAGCUCGUGUUGUGAAAUGUUGGGUUAAGUCCCGCAACGAGCGCAACCCUUA'
'UCCUUGUUUGCCAGCGAGUCAUGUCGGGAACUCCAGGGAGACUGCCGGUGAUAAACCGGAGG'
'AAGGUGGGGACGACGUCAAGUCAUCAUGGCCCUUACGAGUAGGGCUACACACGUGCUACAAU'
'GGCGCAUACAGAGGGCAGCAAGCUAGCGAUAGUGAGCGAAUCCCAAAAAGUGCGUCGUAGUC'
'CGGAUUGGAGUCUGCAACUCGACUCCAUGAAGUCGGAAUCGCUAGUAAUCGUAGAUCAGAAU'
'GCUACGGUGAAUACGUUCCCGGGCCUUGUACACACCGCCCGUCACACCAUGGGAGUGGGCUG'
'CAAAAGAAGUGGGUAGUUUAACCUUUCGGGGAGGACGCUCACCACUUUGUGGUUCAUGACUG'
'GGGUGAAGUCGUAACAAGGUAGCGCUAGGGGAACCUGGCGCUGGAUCACCUCCUUA',
{'DATE': ['02-JUN-2014 (Rel. 121, Created)',
'04-FEB-2016 (Rel. 127, Last updated, Version 5)'],
'DBSOURCE': 'SILVA-LSU; LK021130. SILVA-SSU; LK021130. MD5; '
'afd116bf2c1a13acbf40d63d82f0218c. BioSample; '
'SAMEA3865288.',
'DEFINITION': 'Vibrio anguillarum 16S rRNA',
'KEYWORDS': '.',
'LOCUS': {'locus_name': 'LK021130.1:74067..75610:rRNA',
'class': 'STD',
'division': 'PRO',
'mol_type': 'genomic DNA',
'shape': 'linear',
'size': 1544,
'unit': 'bp',
'version': 1,
'date': '04-FEB-2016'},
'PARENT_ACCESSION': 'LK021130.1',
'VERSION': 'LK021130.1',
'PROJECT_IDENTIFIER': 'Project:PRJEB5701;',
'REFERENCE': [
{'AUTHORS': 'Holm K.;',
'JOURNAL': 'Submitted (26-MAR-2014) to the INSDC. '
'Norstruct, Dept of Chemistry, University of '
'Tromso, Science Park 3, NO-9037 Tromso, NORWAY.',
'TITLE': ';',
'REFERENCE': '1'},
{'AUTHORS': 'Holm K.O., Nilsson K., Hjerde E., Willassen '
'N.P., Milton D.L.;',
'JOURNAL': 'Stand Genomic Sci. 10:60-60(2015).',
'TITLE': '"Complete genome sequence of Vibrio anguillarum '
'strain NB10, a virulent isolate from the Gulf '
'of Bothnia";',
'REFERENCE': '2',
'PUBMED': '26380645'}],
'CROSS_REFERENCE': [
None,
'DOI; 10.1186/s40793-015-0060-7. PUBMED; 26380645.'],
'SOURCE': {
'ORGANISM': 'Vibrio anguillarum',
'taxonomy': 'Bacteria; Proteobacteria; Gammaproteobacteria; '
'Vibrionales; Vibrionaceae; Vibrio.'}},
None,
RNA)
# get the feature level file without FT
self.feature_level_fp = get_data_path(
"embl_feature_level_record_no_FT")
# get a genbank file in order to to file conversion
self.genbank_fp = get_data_path('genbank_single_record')
# a embl constructed sequence file path
self.embl_constructed_fp = get_data_path("embl_constructed")
# a simple embl version to perform embl->gb->embl conversion
self.single_rna_simple_fp = get_data_path(
"embl_single_record_simple")
def setUp(self):
# test locus line
self.locus = (
(['LOCUS NC_005816 9609 bp '
'DNA circular CON 07-FEB-2015'],
{'division': 'CON', 'mol_type': 'DNA', 'shape': 'circular',
'locus_name': 'NC_005816', 'date': '07-FEB-2015',
'unit': 'bp', 'size': 9609}),
(['LOCUS SCU49845 5028 bp '
'DNA PLN 21-JUN-1999'],
{'division': 'PLN', 'mol_type': 'DNA', 'shape': None,
'locus_name': 'SCU49845', 'date': '21-JUN-1999',
'unit': 'bp', 'size': 5028}),
(['LOCUS NP_001832 360 aa '
'linear PRI 18-DEC-2001'],
{'division': 'PRI', 'mol_type': None, 'shape': 'linear',
'locus_name': 'NP_001832', 'date': '18-DEC-2001',
'unit': 'aa', 'size': 360}))
# test single record and read uppercase sequence
self.single_upper_fp = get_data_path('genbank_single_record_upper')
self.single_lower_fp = get_data_path('genbank_single_record_lower')
self.single = (
'GSREILDFK',
{'LOCUS': {'date': '23-SEP-1994',
'division': 'BCT',
'locus_name': 'AAB29917',
'mol_type': None,
'shape': 'linear',
'size': 9,
'unit': 'aa'}},
None,
Protein)
self.single_rna_fp = get_data_path('genbank_single_record')
imd = IntervalMetadata(63)
imd.add([(0, 63)],
[(False, False)],
{'db_xref': '"taxon:562"',
'mol_type': '"mRNA"',
'organism': '"Escherichia coli"',
'type': 'source',
'strand': '+',
'__location': '1..63'})
imd.add([(0, 63)],
[(False, True)],
{'phase': 0,
'db_xref': ['"taxon:562"', '"taxon:561"'],
'__location': '1..>63',
'strand': '+',
'note': '"alkaline phosphatase signal peptide"',
'protein_id': '"AAA23431.1"',
'transl_table': '11',
'translation': '"MKQSTIALAVLPLLFTPVTKA"',
'type': 'CDS'})
self.single_rna = (
'gugaaacaaagcacuauugcacuggcugucuuaccguuacuguuuaccccugugacaaaagcc',
{'ACCESSION': 'M14399',
'COMMENT': 'Original source text: E.coli, cDNA to mRNA.',
'DEFINITION': "alkaline phosphatase signal mRNA, 5' end.",
'KEYWORDS': 'alkaline phosphatase; signal peptide.',
'LOCUS': {'date': '26-APR-1993',
'division': 'BCT',
'locus_name': 'ECOALKP',
'mol_type': 'mRNA',
'shape': 'linear',
'size': 63,
'unit': 'bp'},
'SOURCE': {'ORGANISM': 'Escherichia coli',
'taxonomy': 'Bacteria; Proteobacteria; '
'Gammaproteobacteria; Enterobacteriales; '
'Enterobacteriaceae; Escherichia.'},
'VERSION': 'M14399.1'},
imd,
RNA)
# test:
# 1. multiple records in one file
# 2. lowercase sequence
# 3. DNA, RNA, Protein type
# 4. variation of formats
self.multi_fp = get_data_path('genbank_multi_records')
imd_pro = IntervalMetadata(9)
imd_pro.add([(0, 9)], [(False, False)],
{'organism': '"Bacteria"',
'type': 'source',
'strand': '+',
'__location': '1..9'},)
imd_pro.add([(0, 9)], [(False, True)],
{'__location': '1..>9',
'product': '"L-carnitine amidase"',
'strand': '+',
'type': 'Protein'})
imd_dna = IntervalMetadata(9)
imd_dna.add([(0, 9)], [(False, False)],
{'country': '"Brazil: Parana, Paranavai"',
'type': 'source',
'strand': '+',
'__location': '1..9',
'environmental_sample': ''})
imd_dna.add([(1, 8)], [(True, True)],
{'__location': 'complement(<2..>8)',
'product': '"16S ribosomal RNA"',
'strand': '-',
'type': 'rRNA'})
self.multi = (
('gsreildfk',
{'ACCESSION': 'AAB29917',
'COMMENT': 'Method: direct peptide sequencing.',
'DBSOURCE': 'accession AAB29917.1',
'DEFINITION': 'L-carnitine amidase {N-terminal}',
'KEYWORDS': '.',
'LOCUS': {'date': '23-SEP-1994',
'division': 'BCT',
'locus_name': 'AAB29917',
'mol_type': None,
'shape': 'linear',
'size': 9,
'unit': 'aa'},
'REFERENCE': [{'AUTHORS': 'Joeres,U. and Kula,M.R.',
'JOURNAL': 'AMB 40 (5), 606-610 (1994)',
'PUBMED': '7764422',
'REFERENCE': '1 (residues 1 to 9)',
'REMARK': 'from the original journal article.',
'TITLE': 'a microbial L-carnitine amidase'},
{'AUTHORS': 'Joeres,U. and Kula,M.R.',
'JOURNAL': 'AMB 40 (5), 606-610 (1994)',
'PUBMED': '7764422',
'REFERENCE': '1 (residues 1 to 9)',
'TITLE': 'a microbial L-carnitine amidase'}],
'SOURCE': {'ORGANISM': 'Bacteria',
'taxonomy': 'Unclassified.'},
'VERSION': 'AAB29917.1 GI:545426'},
imd_pro,
Protein),
('catgcaggc',
{'ACCESSION': 'HQ018078',
'DEFINITION': 'Uncultured Xylanimonas sp.16S, partial',
'KEYWORDS': 'ENV.',
'LOCUS': {'date': '29-AUG-2010',
'division': 'ENV',
'locus_name': 'HQ018078',
'mol_type': 'DNA',
'shape': 'linear',
'size': 9,
'unit': 'bp'},
'SOURCE': {'ORGANISM': 'uncultured Xylanimonas sp.',
'taxonomy': 'Bacteria; Actinobacteria; '
'Micrococcales; Promicromonosporaceae; '
'Xylanimonas; environmental samples.'},
'VERSION': 'HQ018078.1 GI:304421728'},
imd_dna,
DNA))
class IntervalMetadataMixinTests:
def _set_up(self):
self.upper_bound = 9
self.im = IntervalMetadata(self.upper_bound)
self.intvls = [
{'bounds': [(0, 1), (2, 9)], 'metadata': {'gene': 'sagA'}},
{'bounds': [(0, 1)], 'metadata': {'gene': ['a'],
'product': 'foo'}}]
def test_constructor_invalid(self):
with self.assertRaisesRegex(TypeError,
'You must provide `IntervalMetadata` '
'object.'):
self._interval_metadata_constructor_(0, '')
def test_constructor_interval_metadata_len_mismatch(self):
for i in [0, 1, 3, 100]:
with self.assertRaisesRegex(
ValueError, '\(%d\).*\(%d\)' % (self.upper_bound, i)):
self._interval_metadata_constructor_(i, self.im)
def test_constructor_interval_metadata_len(self):
for n in 1, 2, 3:
im = IntervalMetadata(n)
im.add([(0, 1)], metadata={'a': 'b'})
obj = self._interval_metadata_constructor_(n, im)
self.assertTrue(obj.has_interval_metadata())
self.assertIsInstance(obj.interval_metadata, IntervalMetadata)
def test_constructor_interval_metadata_len_0(self):
im = IntervalMetadata(0)
obj = self._interval_metadata_constructor_(0, im)
self.assertFalse(obj.has_interval_metadata())
def test_constructor_no_interval_metadata(self):
for i, im in [(0, None), (self.upper_bound, self.im)]:
obj = self._interval_metadata_constructor_(i, im)
self.assertFalse(obj.has_interval_metadata())
self.assertIsInstance(obj.interval_metadata, IntervalMetadata)
def test_constructor_handles_missing_interval_metadata_efficiently(self):
obj = self._interval_metadata_constructor_(self.upper_bound)
self.assertIsNone(obj._interval_metadata)
obj = self._interval_metadata_constructor_(
self.upper_bound, interval_metadata=None)
self.assertIsNone(obj._interval_metadata)
def test_constructor_makes_shallow_copy_of_interval_metadata(self):
intvl = self.im.add(**self.intvls[1])
obj = self._interval_metadata_constructor_(self.upper_bound, self.im)
self.assertEqual(obj.interval_metadata, self.im)
self.assertIsNot(obj.interval_metadata, self.im)
# Changing mutable value of metadata of the old interval
# also changes obj.
intvl.metadata['gene'].append('b')
self.assertEqual(obj.interval_metadata, self.im)
# Changing old interval doesn't change obj
intvl.bounds = [(3, 6)]
self.assertNotEqual(obj.interval_metadata, self.im)
def test_eq_basic(self):
im1 = IntervalMetadata(self.upper_bound)
im1.add(**self.intvls[0])
obj1 = self._interval_metadata_constructor_(self.upper_bound, im1)
im2 = IntervalMetadata(self.upper_bound)
im2.add(**self.intvls[0])
obj2 = self._interval_metadata_constructor_(self.upper_bound, im2)
self.assertReallyEqual(obj1, obj2)
def test_eq_populated_differently(self):
im1 = IntervalMetadata(self.upper_bound)
im1.add(**self.intvls[0])
obj1 = self._interval_metadata_constructor_(self.upper_bound, im1)
obj2 = self._interval_metadata_constructor_(self.upper_bound)
obj2.interval_metadata.add(**self.intvls[0])
self.assertReallyEqual(obj1, obj2)
def test_eq_handles_missing_positional_metadata_efficiently(self):
obj1 = self._interval_metadata_constructor_(self.upper_bound)
obj2 = self._interval_metadata_constructor_(self.upper_bound)
self.assertReallyEqual(obj1, obj2)
self.assertIsNone(obj1._interval_metadata)
self.assertIsNone(obj2._interval_metadata)
def test_ne_diff_len(self):
obj1 = self._interval_metadata_constructor_(0)
obj2 = self._interval_metadata_constructor_(self.upper_bound)
self.assertReallyNotEqual(obj1, obj2)
def test_ne_only_one_is_empty(self):
im1 = IntervalMetadata(self.upper_bound)
im1.add(**self.intvls[0])
obj1 = self._interval_metadata_constructor_(self.upper_bound, im1)
obj2 = self._interval_metadata_constructor_(self.upper_bound)
self.assertReallyNotEqual(obj1, obj2)
def test_ne(self):
im1 = IntervalMetadata(self.upper_bound)
im1.add(**self.intvls[0])
obj1 = self._interval_metadata_constructor_(self.upper_bound, im1)
im2 = IntervalMetadata(self.upper_bound)
im2.add(**self.intvls[1])
obj2 = self._interval_metadata_constructor_(self.upper_bound, im2)
self.assertReallyNotEqual(obj1, obj2)
def test_copy_interval_metadata_empty(self):
obj = self._interval_metadata_constructor_(self.upper_bound, self.im)
obj_copy = copy.copy(obj)
self.assertEqual(obj, obj_copy)
self.assertIsNot(obj, obj_copy)
self.assertIsNone(obj_copy._interval_metadata)
self.assertEqual(obj._interval_metadata, self.im)
def test_copy_interval_metadata_none(self):
obj = self._interval_metadata_constructor_(self.upper_bound)
obj_copy = copy.copy(obj)
self.assertEqual(obj, obj_copy)
self.assertIsNot(obj, obj_copy)
self.assertIsNone(obj._interval_metadata)
self.assertIsNone(obj_copy._interval_metadata)
def test_copy_interval_metadata(self):
self.im.add(**self.intvls[1])
obj = self._interval_metadata_constructor_(self.upper_bound, self.im)
obj_copy = copy.copy(obj)
self.assertEqual(obj, obj_copy)
self.assertIsNot(obj, obj_copy)
self.assertIsNot(obj.interval_metadata,
obj_copy.interval_metadata)
self.assertIsNot(obj.interval_metadata._intervals,
obj_copy.interval_metadata._intervals)
for i, j in zip(obj.interval_metadata._intervals,
obj_copy.interval_metadata._intervals):
self.assertIsNot(i, j)
self.assertIsNot(i.metadata, j.metadata)
for k in i.metadata:
self.assertIs(i.metadata[k], j.metadata[k])
def test_deepcopy_interval_metadata(self):
self.im.add(**self.intvls[1])
obj = self._interval_metadata_constructor_(self.upper_bound, self.im)
obj_copy = copy.deepcopy(obj)
self.assertEqual(obj, obj_copy)
self.assertIsNot(obj, obj_copy)
self.assertIsNot(obj.interval_metadata,
obj_copy.interval_metadata)
self.assertIsNot(obj.interval_metadata._intervals,
obj_copy.interval_metadata._intervals)
for i, j in zip(obj.interval_metadata._intervals,
obj_copy.interval_metadata._intervals):
self.assertIsNot(i, j)
self.assertIsNot(i.metadata, j.metadata)
self.assertIsNot(i.metadata['gene'], j.metadata['gene'])
self.assertIs(i.metadata['product'], j.metadata['product'])
def test_deepcopy_interval_metadata_empty(self):
obj = self._interval_metadata_constructor_(self.upper_bound, self.im)
obj_copy = copy.deepcopy(obj)
self.assertEqual(obj, obj_copy)
self.assertIsNot(obj, obj_copy)
self.assertIsNone(obj_copy._interval_metadata)
self.assertEqual(obj._interval_metadata, self.im)
def test_deepcopy_interval_metadata_none(self):
obj = self._interval_metadata_constructor_(self.upper_bound, None)
obj_copy = copy.deepcopy(obj)
self.assertEqual(obj, obj_copy)
self.assertIsNot(obj, obj_copy)
self.assertIsNone(obj._interval_metadata)
self.assertIsNone(obj_copy._interval_metadata)
def test_deepcopy_memo_is_respected(self):
# Basic test to ensure deepcopy's memo is passed through to recursive
# deepcopy calls.
obj = self._interval_metadata_constructor_(self.upper_bound, self.im)
memo = {}
copy.deepcopy(obj, memo)
self.assertGreater(len(memo), 1)
def test_interval_metadata_getter(self):
self.im.add(**self.intvls[0])
obj = self._interval_metadata_constructor_(self.upper_bound, self.im)
self.assertIsInstance(obj.interval_metadata, IntervalMetadata)
self.assertEqual(self.im, obj.interval_metadata)
# Update existing metadata.
obj.interval_metadata._intervals[0].metadata['gene'] = 'sagB'
self.assertNotEqual(obj.interval_metadata, self.im)
self.im._intervals[0].metadata['gene'] = 'sagB'
self.assertEqual(obj.interval_metadata, self.im)
# Add new interval feature.
obj.interval_metadata.add(**self.intvls[1])
self.im.add(**self.intvls[1])
self.assertEqual(obj.interval_metadata, self.im)
def test_interval_metadata_getter_no_interval_metadata(self):
obj = self._interval_metadata_constructor_(self.upper_bound)
self.assertIsNone(obj._interval_metadata)
self.assertIsInstance(obj.interval_metadata, IntervalMetadata)
self.assertEqual(obj.interval_metadata, self.im)
self.assertIsNotNone(obj._interval_metadata)
def test_interval_metadata_setter(self):
obj = self._interval_metadata_constructor_(self.upper_bound)
self.assertFalse(obj.has_interval_metadata())
obj.interval_metadata = self.im
self.assertFalse(obj.has_interval_metadata())
self.assertEqual(obj.interval_metadata, self.im)
self.im.add(**self.intvls[1])
obj.interval_metadata = self.im
self.assertTrue(obj.has_interval_metadata())
self.assertEqual(obj.interval_metadata, self.im)
def test_interval_metadata_setter_makes_copy(self):
intvl = self.im.add(**self.intvls[1])
obj = self._interval_metadata_constructor_(self.upper_bound)
obj.interval_metadata = self.im
self.assertEqual(obj.interval_metadata, self.im)
self.assertIsNot(obj.interval_metadata, self.im)
# Changing mutable value of metadata of the old interval
# also changes obj.
intvl.metadata['gene'].append('b')
self.assertEqual(obj.interval_metadata, self.im)
# Changing old interval doesn't change obj
intvl.bounds = [(3, 6)]
self.assertNotEqual(obj.interval_metadata, self.im)
def test_interval_metadata_setter_len_mismatch(self):
self.im.add(**self.intvls[1])
obj = self._interval_metadata_constructor_(self.upper_bound, self.im)
for i in 0, 1, 3, 100:
with self.assertRaisesRegex(
ValueError, '\(%d\).*\(%d\)' % (i, self.upper_bound)):
obj.interval_metadata = IntervalMetadata(i)
self.assertEqual(obj.interval_metadata, self.im)
def test_interval_metadata_setter_invalid_type(self):
self.im.add(**self.intvls[0])
obj = self._interval_metadata_constructor_(self.upper_bound, self.im)
for i in [2, None, '', {}, []]:
with self.assertRaisesRegex(
TypeError,
'You must provide `IntervalMetadata` object'):
obj.interval_metadata = i
self.assertEqual(self.im, obj.interval_metadata)
def test_interval_metadata_deleter_empty(self):
obj = self._interval_metadata_constructor_(self.upper_bound, self.im)
del obj.interval_metadata
self.assertIsNone(obj._interval_metadata)
self.assertFalse(obj.has_interval_metadata())
# Delete again. test idempotent
del obj.interval_metadata
self.assertIsNone(obj._interval_metadata)
self.assertFalse(obj.has_interval_metadata())
def test_interval_metadata_deleter(self):
self.im.add(**self.intvls[0])
obj = self._interval_metadata_constructor_(self.upper_bound, self.im)
del obj.interval_metadata
self.assertIsNone(obj._interval_metadata)
self.assertFalse(obj.has_interval_metadata())
def test_has_interval_metadata(self):
obj = self._interval_metadata_constructor_(self.upper_bound)
self.assertFalse(obj.has_interval_metadata())
obj = self._interval_metadata_constructor_(self.upper_bound, self.im)
self.assertFalse(obj.has_interval_metadata())
self.im.add([(0, 1)])
obj = self._interval_metadata_constructor_(self.upper_bound, self.im)
self.assertTrue(obj.has_interval_metadata())
class TestIntervalMetadata(unittest.TestCase, ReallyEqualMixin):
def setUp(self):
self.upper_bound = 10
self.im_empty = IntervalMetadata(self.upper_bound)
self.im_1 = IntervalMetadata(self.upper_bound)
self.im_1_1 = Interval(
interval_metadata=self.im_1,
bounds=[(1, 2), (4, self.upper_bound)],
metadata={'gene': 'sagA', 'bound': 0})
self.im_2 = IntervalMetadata(self.upper_bound)
self.im_2_1 = Interval(
interval_metadata=self.im_2,
bounds=[(1, 2), (4, self.upper_bound)],
metadata={'gene': 'sagA', 'bound': 0})
self.im_2_2 = Interval(
interval_metadata=self.im_2,
bounds=[(3, 5)],
metadata={'gene': 'sagB', 'bound': 0, 'spam': [0]})
def test_copy_empty(self):
obs = copy(self.im_empty)
self.assertEqual(obs, self.im_empty)
self.assertIsNot(obs._intervals, self.im_empty._intervals)
self.assertIsNot(obs._interval_tree, self.im_empty._interval_tree)
def test_copy(self):
obs = copy(self.im_2)
self.assertEqual(obs, self.im_2)
self.assertIsNot(obs._intervals, self.im_2._intervals)
self.assertIsNot(obs._interval_tree, self.im_2._interval_tree)
for i in range(self.im_2.num_interval_features):
i1, i2 = obs._intervals[i], self.im_2._intervals[i]
self.assertIsNot(i1, i2)
self.assertIsNot(i1.bounds, i2.bounds)
self.assertIsNot(i1.fuzzy, i2.fuzzy)
self.assertIsNot(i1._interval_metadata, i2._interval_metadata)
self.assertIsNot(i1.metadata, i2.metadata)
for k in i1.metadata:
self.assertIs(i1.metadata[k], i2.metadata[k])
def test_deepcopy(self):
obs = deepcopy(self.im_2)
self.assertEqual(obs, self.im_2)
self.assertIsNot(obs._intervals, self.im_2._intervals)
self.assertIsNot(obs._interval_tree, self.im_2._interval_tree)
for i in range(self.im_2.num_interval_features):
i1, i2 = obs._intervals[i], self.im_2._intervals[i]
self.assertIsNot(i1, i2)
self.assertIsNot(i1.bounds, i2.bounds)
self.assertIsNot(i1.fuzzy, i2.fuzzy)
self.assertIsNot(i1.metadata, i2.metadata)
i2.metadata['spam'].append(1)
self.assertEqual(i2.metadata,
{'gene': 'sagB', 'bound': 0, 'spam': [0, 1]})
self.assertEqual(i1.metadata,
{'gene': 'sagB', 'bound': 0, 'spam': [0]})
def test_deepcopy_memo_is_respected(self):
memo = {}
deepcopy(self.im_1, memo)
self.assertGreater(len(memo), 2)
def test_init(self):
self.assertFalse(self.im_empty._is_stale_tree)
self.assertEqual(self.im_empty._intervals, [])
def test_init_upper_bound_lt_lower_bound(self):
# test that no exception is raised
IntervalMetadata(0)
with self.assertRaises(ValueError):
IntervalMetadata(-1)
def test_num_interval_features(self):
self.assertEqual(self.im_empty.num_interval_features, 0)
self.assertEqual(self.im_1.num_interval_features, 1)
self.assertEqual(self.im_2.num_interval_features, 2)
def test_duplicate(self):
'''Test query and drop methods on duplicate Intervals.'''
intvl_1 = self.im_empty.add([(1, 2)])
intvl_2 = self.im_empty.add([(1, 2)])
self.assertEqual(len(list(self.im_empty.query([(1, 2)]))), 2)
self.im_empty.drop([intvl_1])
self.assertEqual(len(self.im_empty._intervals), 1)
self.assertTrue(self.im_empty._intervals[0] is intvl_2)
def test_duplicate_bounds(self):
intvl = self.im_empty.add([(1, 2), (1, 2)])
intvls = list(self.im_empty.query([(1, 2)]))
self.assertEqual(len(intvls), 1)
self.assertTrue(intvl is intvls[0])
def test_concat_empty(self):
for i in 0, 1, 2:
obs = IntervalMetadata.concat([self.im_empty] * i)
exp = IntervalMetadata(self.upper_bound * i)
self.assertEqual(obs, exp)
obs = IntervalMetadata.concat([])
self.assertEqual(obs, IntervalMetadata(0))
def test_concat(self):
im1 = IntervalMetadata(3)
im2 = IntervalMetadata(4)
im3 = IntervalMetadata(5)
im1.add([(0, 2)], [(True, True)])
im2.add([(0, 3)], [(True, False)], {'gene': 'sagA'})
im2.add([(2, 4)], metadata={'gene': 'sagB'})
im3.add([(1, 5)], [(False, True)], {'gene': 'sagC'})
obs = IntervalMetadata.concat([im1, im2, im3])
exp = IntervalMetadata(12)
exp.add(bounds=[(0, 2)], fuzzy=[(True, True)])
exp.add(bounds=[(3, 6)], fuzzy=[(True, False)],
metadata={'gene': 'sagA'})
exp.add(bounds=[(5, 7)], metadata={'gene': 'sagB'})
exp.add(bounds=[(8, 12)], fuzzy=[(False, True)],
metadata={'gene': 'sagC'})
self.assertEqual(obs, exp)
def test_sort(self):
interval = Interval(
self.im_2,
[(1, 2), (3, 8)],
metadata={'gene': 'sagA', 'bound': 0})
im = deepcopy(self.im_2)
self.im_2.sort(False)
# check sorting does not have other side effects
self.assertEqual(im, self.im_2)
self.assertEqual(self.im_2._intervals,
[self.im_2_2, self.im_2_1, interval])
self.im_2.sort()
self.assertEqual(im, self.im_2)
self.assertEqual(self.im_2._intervals,
[interval, self.im_2_1, self.im_2_2])
self.im_empty.sort()
self.assertEqual(self.im_empty, IntervalMetadata(self.upper_bound))
def test_add_eq_upper_bound(self):
self.im_empty.add(bounds=[(1, 2), (4, self.upper_bound)],
metadata={'gene': 'sagA', 'bound': 0})
self.assertTrue(self.im_empty._is_stale_tree)
interval = self.im_empty._intervals[0]
self.assertEqual(interval.bounds, [(1, 2), (4, self.upper_bound)])
self.assertEqual(interval.metadata, {'gene': 'sagA', 'bound': 0})
self.assertTrue(isinstance(self.im_empty._interval_tree, IntervalTree))
def test_add_gt_upper_bound(self):
with self.assertRaises(ValueError):
self.im_empty.add(bounds=[(1, 2), (4, self.upper_bound+1)],
metadata={'gene': 'sagA', 'bound': 0})
def test_add_eq_start_end_bound(self):
for i in 0, 1, self.upper_bound:
# test that no exception is raised
self.im_empty.add(bounds=[(i, i)],
metadata={'gene': 'sagA', 'bound': 0})
def test_query_attribute(self):
intervals = self.im_2._query_attribute({})
for i, j in zip(intervals, self.im_2._intervals):
self.assertEqual(i, j)
intervals = list(self.im_2._query_attribute(None))
self.assertEqual(len(intervals), 0)
for i in self.im_2._intervals:
intervals = list(self.im_2._query_attribute(i.metadata))
self.assertEqual(len(intervals), 1)
self.assertEqual(intervals[0], i)
def test_query_interval(self):
intervals = list(self.im_2._query_interval((1, 2)))
self.assertEqual(len(intervals), 1)
self.assertEqual(intervals[0], self.im_2_1)
intervals = list(self.im_2._query_interval((3, 4)))
self.assertEqual(len(intervals), 1)
self.assertEqual(intervals[0], self.im_2_2)
intervals = {repr(i) for i in self.im_2._query_interval((1, 7))}
self.assertEqual(len(intervals), 2)
self.assertSetEqual(intervals,
{repr(i) for i in self.im_2._intervals})
def test_query_interval_upper_bound(self):
intervals = list(self.im_2._query_interval((self.upper_bound-1,
self.upper_bound)))
self.assertEqual(intervals, [self.im_2_1])
def test_query(self):
intervals = list(self.im_2.query(bounds=[(1, 5)],
metadata={'gene': 'sagA'}))
self.assertEqual(len(intervals), 1)
self.assertEqual(intervals[0], self.im_2_1)
def test_query_empty(self):
intervals = list(self.im_1.query())
self.assertEqual(len(intervals), 0)
def test_query_no_hits(self):
intervals = list(self.im_2.query(bounds=[(self.upper_bound, 200)]))
self.assertEqual(len(intervals), 0)
intervals = list(self.im_2.query(metadata={'gene': 'sagC'}))
self.assertEqual(len(intervals), 0)
intervals = list(self.im_2.query(bounds=[(1, 2)],
metadata={'gene': 'sagC'}))
self.assertEqual(len(intervals), 0)
def test_query_interval_only(self):
for loc in [[(1, 7)],
[(1, 2), (3, 4)]]:
intervals = list(self.im_2.query(bounds=loc))
self.assertEqual(len(intervals), 2)
self.assertEqual(intervals[0], self.im_2_1)
self.assertEqual(intervals[1], self.im_2_2)
def test_query_metadata_only(self):
intervals = list(self.im_2.query(metadata={'gene': 'sagB'}))
self.assertEqual(len(intervals), 1)
self.assertEqual(intervals[0], self.im_2_2)
intervals = list(self.im_2.query(metadata={'bound': 0}))
self.assertEqual(len(intervals), 2)
self.assertEqual(intervals[0], self.im_2_1)
self.assertEqual(intervals[1], self.im_2_2)
def test_drop(self):
intvl = self.im_2._intervals[0]
self.im_2.drop([intvl])
self.assertEqual(len(self.im_2._intervals), 1)
self.assertEqual(self.im_2._intervals[0], self.im_2_2)
# test the intvl was set to dropped
self.assertTrue(intvl.dropped)
def test_drop_all(self):
self.im_2.drop(self.im_2._intervals)
self.assertEqual(self.im_2, self.im_empty)
def test_reverse(self):
self.im_2._reverse()
Interval(
interval_metadata=self.im_empty,
bounds=[(0, 6), (8, 9)],
metadata={'gene': 'sagA', 'bound': 0})
Interval(
interval_metadata=self.im_empty,
bounds=[(5, 7)],
metadata={'gene': 'sagB', 'bound': 0, 'spam': [0]})
self.assertEqual(self.im_2, self.im_empty)
def test_eq_ne(self):
im1 = IntervalMetadata(10)
im1.add(metadata={'gene': 'sagA', 'bound': '0'},
bounds=[(0, 2), (4, 7)])
im1.add(metadata={'gene': 'sagB', 'bound': '3'},
bounds=[(3, 5)])
# The ordering shouldn't matter
im2 = IntervalMetadata(10)
im2.add(metadata={'gene': 'sagB', 'bound': '3'},
bounds=[(3, 5)])
im2.add(metadata={'gene': 'sagA', 'bound': '0'},
bounds=[(0, 2), (4, 7)])
im3 = IntervalMetadata(10)
im3.add(metadata={'gene': 'sagA', 'bound': '3'},
bounds=[(0, 2), (4, 7)])
im3.add(metadata={'gene': 'sagB', 'bound': '3'},
bounds=[(3, 5)])
self.assertReallyEqual(im1, im2)
self.assertReallyNotEqual(im1, im3)
def test_ne_diff_bounds(self):
im1 = IntervalMetadata(10)
im2 = IntervalMetadata(9)
intvl = {'bounds': [(0, 1)], 'metadata': {'spam': 'foo'}}
im1.add(**intvl)
im2.add(**intvl)
self.assertReallyNotEqual(im1, im2)
def test_repr(self):
exp = '''0 interval features
-------------------'''
self.assertEqual(repr(self.im_empty), exp)
self.im_empty.add([(1, 2)], metadata={'gene': 'sagA'})
exp = '''1 interval feature
------------------
Interval\(interval_metadata=<[0-9]+>, bounds=\[\(1, 2\)\], \
fuzzy=\[\(False, False\)\], metadata={'gene': 'sagA'}\)'''
self.assertRegex(repr(self.im_empty), exp)
self.im_empty.add([(3, 4)], metadata={'gene': 'sagB'})
self.im_empty.add([(3, 4)], metadata={'gene': 'sagC'})
self.im_empty.add([(3, 4)], metadata={'gene': 'sagD'})
self.im_empty.add([(3, 4)], metadata={'gene': 'sagE'})
self.im_empty.add([(3, 4)], metadata={'gene': 'sagF'})
exp = '''6 interval features
-------------------
Interval\(interval_metadata=<[0-9]+>, bounds=\[\(1, 2\)\], \
fuzzy=\[\(False, False\)\], metadata={'gene': 'sagA'}\)
Interval\(interval_metadata=<[0-9]+>, bounds=\[\(3, 4\)\], \
fuzzy=\[\(False, False\)\], metadata={'gene': 'sagB'}\)
...
Interval\(interval_metadata=<[0-9]+>, bounds=\[\(3, 4\)\], \
fuzzy=\[\(False, False\)\], metadata={'gene': 'sagE'}\)
Interval\(interval_metadata=<[0-9]+>, bounds=\[\(3, 4\)\], \
fuzzy=\[\(False, False\)\], metadata={'gene': 'sagF'}\)'''
self.assertRegex(repr(self.im_empty), exp)
def test_concat(self):
im1 = IntervalMetadata(3)
im2 = IntervalMetadata(4)
im3 = IntervalMetadata(5)
im1.add([(0, 2)], [(True, True)])
im2.add([(0, 3)], [(True, False)], {'gene': 'sagA'})
im2.add([(2, 4)], metadata={'gene': 'sagB'})
im3.add([(1, 5)], [(False, True)], {'gene': 'sagC'})
obs = IntervalMetadata.concat([im1, im2, im3])
exp = IntervalMetadata(12)
exp.add(bounds=[(0, 2)], fuzzy=[(True, True)])
exp.add(bounds=[(3, 6)], fuzzy=[(True, False)],
metadata={'gene': 'sagA'})
exp.add(bounds=[(5, 7)], metadata={'gene': 'sagB'})
exp.add(bounds=[(8, 12)], fuzzy=[(False, True)],
metadata={'gene': 'sagC'})
self.assertEqual(obs, exp)
def test_concat(self):
im1 = IntervalMetadata(3)
im2 = IntervalMetadata(4)
im3 = IntervalMetadata(5)
im1.add([(0, 2)], [(True, True)])
im2.add([(0, 3)], [(True, False)], {'gene': 'sagA'})
im2.add([(2, 4)], metadata={'gene': 'sagB'})
im3.add([(1, 5)], [(False, True)], {'gene': 'sagC'})
obs = IntervalMetadata.concat([im1, im2, im3])
exp = IntervalMetadata(12)
exp.add(bounds=[(0, 2)], fuzzy=[(True, True)])
exp.add(bounds=[(3, 6)],
fuzzy=[(True, False)],
metadata={'gene': 'sagA'})
exp.add(bounds=[(5, 7)], metadata={'gene': 'sagB'})
exp.add(bounds=[(8, 12)],
fuzzy=[(False, True)],
metadata={'gene': 'sagC'})
self.assertEqual(obs, exp)
def test_eq_ne(self):
im1 = IntervalMetadata(10)
im1.add(metadata={
'gene': 'sagA',
'bound': '0'
},
bounds=[(0, 2), (4, 7)])
im1.add(metadata={'gene': 'sagB', 'bound': '3'}, bounds=[(3, 5)])
# The ordering shouldn't matter
im2 = IntervalMetadata(10)
im2.add(metadata={'gene': 'sagB', 'bound': '3'}, bounds=[(3, 5)])
im2.add(metadata={
'gene': 'sagA',
'bound': '0'
},
bounds=[(0, 2), (4, 7)])
im3 = IntervalMetadata(10)
im3.add(metadata={
'gene': 'sagA',
'bound': '3'
},
bounds=[(0, 2), (4, 7)])
im3.add(metadata={'gene': 'sagB', 'bound': '3'}, bounds=[(3, 5)])
self.assertReallyEqual(im1, im2)
self.assertReallyNotEqual(im1, im3)
class GFF3IOTests(TestCase):
def setUp(self):
self.multi_fp = get_data_path('gff3_multi_record')
self.single_fp = get_data_path('gff3_single_record')
intvls = [{
'bounds': [(0, 4641652)],
'metadata': {
'source': 'European Nucleotide Archive',
'type': 'chromosome',
'score': '.',
'strand': '.',
'ID': 'chromosome:Chromosome',
'Alias': 'U00096.3',
'Is_circular': 'true'
}
}, {
'bounds': [(147, 148)],
'metadata': {
'source': 'regulondb_feature',
'type': 'biological_region',
'score': '.',
'strand': '+',
'external_name': 'Promoter thrLp (RegulonDB:ECK120010236)',
'logic_name': 'regulondb_promoter'
}
}, {
'bounds': [(336, 2799)],
'metadata': {
'source': 'Prodigal_v2.60',
'type': 'gene',
'score': '1.8',
'strand': '+',
'phase': 0,
'ID': '1_1',
'gc_cont': '0.427'
}
}, {
'bounds': [(336, 2799)],
'metadata': {
'source': 'Prodigal_v2.60',
'type': 'CDS',
'score': '333.8',
'strand': '+',
'phase': 0,
'ID': '1_2',
'Parent': '1_1',
'rbs_motif': 'GGAG/GAGG',
'rbs_spacer': '5-10bp'
}
}, {
'bounds': [(0, 50), (55, 100)],
'metadata': {
'source': 'Prodigal_v2.60',
'type': 'gene',
'score': '1.8',
'strand': '+',
'phase': 0,
'ID': '1_1',
'gene': 'FXR receptor'
}
}]
self.upper_bound = 4641652
self.imd1 = IntervalMetadata(self.upper_bound)
self.imd1.add(**intvls[0])
self.imd1.add(**intvls[1])
self.imd2 = IntervalMetadata(None)
self.imd2.add(**intvls[2])
self.imd2.add(**intvls[3])
self.imd3 = IntervalMetadata(None)
self.imd3.add(**intvls[4])
self.seq_fp = get_data_path('gff3_dna')
self.seq = Sequence('ATGCATGCATGC',
metadata={
'id': 'NC_1',
'description': 'species X'
})
self.seq.interval_metadata.add(
[(0, 9)],
metadata={
'source': 'Prodigal_v2.60',
'type': 'gene',
'score': '.',
'strand': '+',
'phase': 0,
'ID': 'gene1',
'Name': 'FXR'
})
self.dna = DNA(self.seq)