def test_cap_enzyme_filter():
'It test the cap enzyme filter'
seq = 'ATGATGATG' + 'gaaattc' + 'ATGATGATGTGGGAT'
alleles = {('AA', INVARIANT):{},
('A', DELETION) :{}}
snv = SeqFeature(type='snv', location=FeatureLocation(10, 11),
qualifiers={'alleles':alleles})
seq = SeqWithQuality(seq=Seq(seq), name='ref', features=[snv])
all_enzymes = True
filter_ = create_cap_enzyme_filter(all_enzymes)
filter_(seq)
for snv, expected in zip(seq.get_features(kind='snv'), [False]):
result = snv.qualifiers['filters']['cap_enzymes'][all_enzymes]
assert result == expected
#No cap
seq = 'ATGATGATG' + 'ATGATGATGTGGGAT'
alleles = {('A', INVARIANT):{},
('A', DELETION) :{}}
snv = SeqFeature(type='snv', location=FeatureLocation(11, 11),
qualifiers={'alleles':alleles})
seq = SeqWithQuality(seq=Seq(seq), name='ref', features=[snv])
all_enzymes = True
filter_ = create_cap_enzyme_filter(all_enzymes)
filter_(seq)
for snv, expected in zip(seq.get_features(kind='snv'), [True]):
result = snv.qualifiers['filters']['cap_enzymes'][all_enzymes]
assert result == expected
def test_kind_filter():
'It test the kind filter'
alleles = {('A', INVARIANT):{},
('T', SNP) :{}}
snv1 = SeqFeature(type='snv', location=FeatureLocation(1, 1),
qualifiers={'reference_allele':'A',
'alleles':alleles})
alleles = {('A', INVARIANT):{},
('TC', INSERTION) :{}}
snv2 = SeqFeature(type='snv', location=FeatureLocation(3, 3),
qualifiers={'reference_allele':'A',
'alleles':alleles})
seq_str = 'AATATA'
seq = SeqWithQuality(seq=Seq(seq_str), qual=[30] * len(seq_str),
features=[snv1, snv2])
kind = SNP
filter_ = create_kind_filter(kind)
filter_(seq)
for snv, expected in zip(seq.get_features(kind='snv'), [False, True]):
result = snv.qualifiers['filters']['by_kind'][kind]
assert result == expected
def test_snv_prot_change_annotator():
'It test the snv_prot_changepolia annotator'
# first annotate orf
seq = 'ATGGCTTCATCCATTCTCTCATCCGCCGNTGTGGCCTTTGNCAACAGGGCTTCCCCTGCTCA'
seq += 'AGCTAGCATGGGGGCACCATTCACTGGCCTAAAATCCGCCGCTGCTTTCCCNGTTTTATGTA'
seq += 'CTGTTTTNACTCGCANGACCAACGACATCACCACTTTGGTTAGCAATGGGGGAAGAGTTCAG'
seq += 'GGCNTGAAGGTGTGCCCACCACTTGGATTGAAGAAGTTCGAGACTCTTTCTTACCTTCCTGA'
seq += 'TATGAGTAACGAGCAATTGGGAAAGGAAGTTGACTACCTTCTCAGGAAGGGATGGATTCCCT'
seq += 'GCATTGAATTCGACATTCACAGTGGATTCGTTTACCGTGAGACCCACAGGTCACCAGGATAC'
seq += 'TTCGATGGACGCTACTGGACCATGTGGAAGCTGCCCATGTTTGGCTGCACCGAT'
orf = 'ATGGCTTCATCCATTCTCTCATCCGCCGNTGTGGCCTTTGNCAACAGGGCTTCCCTGCTCAA'
orf += 'GCTAGCATGGGGGCACCATTCACTGGCCTAAAATCCGCCGCTGCTTTCCCNGTNACTCGCAN'
orf += 'GACCAACGACATCACCACTTTGGTTAGCAATGGGGGAAGAGTTCAGGGCNTGAAGGTGTGCC'
orf += 'CACCACTTGGATTGAAGAAGTTCGAGACTCTTTCTTACCTTCCTGATATGAGTAACGAGCAA'
orf += 'TTGGGAAAGGAAGTTGACTACCTTCTCAGGAAGGGATGGATTCCCTGCATTGAATTCGACAT'
orf += 'TCACAGTGGATTCGTTTACCGTGAGACCCACAGGTCACCAGGATACTTCGATGGACGCTAC'
orf += 'TGGACCATGTGGAAGCTGCCCATGTTTGGCTGCACCGAT'
qualifiers = {'strand':'forward', 'dna':Seq(orf), 'prot':'prot'}
feature = SeqFeature(location=FeatureLocation(0, len(seq)), type='orf',
qualifiers=qualifiers)
alleles = {('A', SNP): None, ('G', INVARIANT):None}
snv = SeqFeature(location=FeatureLocation(24, 24), type='snv',
qualifiers = {'alleles':alleles})
alleles = {('A', SNP): None, ('T', INVARIANT):None}
snv2 = SeqFeature(location=FeatureLocation(56, 56), type='snv',
qualifiers = {'alleles':alleles})
alleles = {('T', SNP): None, ('A', INVARIANT):None}
snv3 = SeqFeature(location=FeatureLocation(399, 399), type='snv',
qualifiers = {'alleles':alleles})
alleles = {('T', INVARIANT):None, ('AG', INSERTION):None}
snv4 = SeqFeature(location=FeatureLocation(250, 250), type='snv',
qualifiers = {'alleles':alleles})
alleles = {('G', INVARIANT):None, ('--', DELETION):None}
snv5 = SeqFeature(location=FeatureLocation(251, 251), type='snv',
qualifiers = {'alleles':alleles})
sequence = SeqWithQuality(seq=Seq(seq), name='query')
#print str(sequence[257:265].seq)
#print sequence[256]
sequence.features = [feature, snv, snv2, snv3, snv4, snv5]
annotator = create_prot_change_annotator()
annotator(sequence)
[feature, snv, snv2, snv3, snv4, snv5] = sequence.features
assert snv.qualifiers['protein_change']['kind'] == 'substitution'
assert snv3.qualifiers['protein_change']['kind'] == 'substitution'
assert snv4.qualifiers['protein_change']['kind'] == 'breakage'
#
assert snv.qualifiers['protein_change']['location'] == 'codon_1'
def test_close_to_seqvar_filter():
'It tests that we can detect snvs by its proximity to another snv'
alleles = {('A', SNP): None, ('T', INVARIANT):None}
snv1 = SeqFeature(type='snv', location=FeatureLocation(1, 1),
qualifiers={'alleles':alleles})
snv2 = SeqFeature(type='snv', location=FeatureLocation(4, 4),
qualifiers={'alleles':alleles})
snv3 = SeqFeature(type='snv', location=FeatureLocation(6, 6),
qualifiers={'alleles':alleles})
seq_str = 'AATATA'
seq = SeqWithQuality(seq=Seq(seq_str), qual=[30] * len(seq_str),
features=[snv1, snv2, snv3])
proximity = 3
filter_ = create_close_to_snv_filter(proximity)
filter_(seq)
for snv, expected in zip(seq.get_features(kind='snv'),
[True, True, True]):
result = snv.qualifiers['filters']['close_to_snv'][(proximity, None, None)]
assert result == expected
snv.qualifiers['filters']['close_to_snv']
alleles2 = {('A', DELETION): None, ('AT', INVARIANT):None}
snv1 = SeqFeature(type='snv', location=FeatureLocation(1, 3),
qualifiers={'reference_allele':'AT',
'alleles':alleles2})
snv2 = SeqFeature(type='snv', location=FeatureLocation(4, 6),
qualifiers={'reference_allele':'AT',
'alleles':alleles2})
snv3 = SeqFeature(type='snv', location=FeatureLocation(6, 8),
qualifiers={'reference_allele':'AT',
'alleles':alleles2})
alleles3 = {('AC', INSERTION): None, ('A', INVARIANT):None}
snv4 = SeqFeature(type='snv', location=FeatureLocation(9, 10),
qualifiers={'reference_allele':'A',
'alleles':alleles3})
seq = SeqWithQuality(seq=Seq(seq_str), qual=[30] * len(seq_str),
features=[snv1, snv2, snv3, snv4])
filter_ = create_close_to_snv_filter(proximity, INDEL)
filter_(seq)
for snv, expected in zip(seq.get_features(kind='snv'),
[True, True, True, True]):
result = snv.qualifiers['filters']['close_to_snv'][(proximity, INDEL, None)]
assert result == expected
def test_major_allele_freq_filter_snv():
'It test the first allele percent filter'
read_groups = {'g1':{}, 'g2':{}}
alleles = {('A', INVARIANT):{'read_groups':{'g1':4}},
('T', SNP) :{'read_groups':{'g2':2}}}
snv1 = SeqFeature(type='snv', location=FeatureLocation(1, 1),
qualifiers={'alleles':alleles,
'read_groups':read_groups})
alleles = {('A', INVARIANT):{'read_groups':{'g1':3}},
('T', SNP) :{'read_groups':{'g2':2}}}
snv2 = SeqFeature(type='snv', location=FeatureLocation(3, 3),
qualifiers={'alleles':alleles,
'read_groups':read_groups})
seq_str = 'AATATA'
seq = SeqWithQuality(seq=Seq(seq_str), qual=[30] * len(seq_str),
features=[snv1, snv2])
frecuency = 0.59999999999999998
filter_ = create_major_allele_freq_filter(frecuency)
filter_(seq)
for snv, expected in zip(seq.get_features(kind='snv'), [True, False]):
result = snv.qualifiers['filters']['maf'][(frecuency, )]
assert result == expected
#now we do it only for one read group
snv1 = SeqFeature(type='snv', location=FeatureLocation(1, 1),
qualifiers={'alleles':alleles,
'read_groups':read_groups})
snv2 = SeqFeature(type='snv', location=FeatureLocation(3, 3),
qualifiers={'alleles':alleles,
'read_groups':read_groups})
seq = SeqWithQuality(seq=Seq(seq_str), qual=[30] * len(seq_str),
features=[snv1, snv2])
frecuency = 0.59999999999999998
filter_ = create_major_allele_freq_filter(frecuency,
groups=['g1'],
group_kind='read_groups')
filter_(seq)
for snv, expected in zip(seq.get_features(kind='snv'), [True, True]):
parameters = (0.59999999999999998, ('g1',), 'read_groups')
result = snv.qualifiers['filters']['maf'][parameters]
assert result == expected
def test_close_to_limit_filter():
'It tests that we can detect snvs close to the limit'
snv1 = SeqFeature(type='snv', location=FeatureLocation(1, 1),
qualifiers={})
snv2 = SeqFeature(type='snv', location=FeatureLocation(4, 4),
qualifiers={})
snv3 = SeqFeature(type='snv', location=FeatureLocation(6, 6),
qualifiers={})
seq_str = 'AATATA'
seq = SeqWithQuality(seq=Seq(seq_str), qual=[30] * len(seq_str),
features=[snv1, snv2, snv3])
distance = 2
filter_ = create_snv_close_to_limit_filter(distance)
filter_(seq)
for snv, expected in zip(seq.get_features(kind='snv'),
[True, False, True]):
result = snv.qualifiers['filters']['close_to_limit'][distance]
assert result == expected
def test_seqs_string():
''' Here we test it we can initialice a seq with quality
and if we can print it. Seq is going to be a normal string'''
#sequence1 = Seq('aaavvttt')
# First we initialice the quality in the init
seq1 = SeqWithQuality(name='seq1', seq=Seq('aaavvttt'),
qual=[2, 4 , 1, 4, 5, 6, 12, 34])
assert seq1
# Here we add the quality after the initialization
seq2 = SeqWithQuality(name='seq2', seq=Seq('aaavvttt'))
seq2.qual = [2, 4 , 1, 4, 5, 6, 12, 34]
assert seq2
# Let's check the sliceability of the seq
for num in range(len(seq1)):
seq3 = seq1[num]
assert seq3
def test_ref_in_list_filter():
'We filter out the snv close to an intron'
snv = SeqFeature(type='snv', location=FeatureLocation(100, 100),
qualifiers={})
seq1 = SeqWithQuality(name='seq1', seq=Seq('A'), features=[snv])
snv1 = SeqFeature(type='snv', location=FeatureLocation(100, 100),
qualifiers={})
seq2 = SeqWithQuality(name='seq2', seq=Seq('A'), features=[snv1])
seq_list = ['seq1']
filter_ = create_reference_in_list_filter(seq_list)
filter_(seq1)
for snv, expected in zip(seq1.get_features(kind='snv'), [True]):
result = snv.qualifiers['filters']['ref_not_in_list'][None]
assert result == expected
filter_(seq2)
for snv, expected in zip(seq2.get_features(kind='snv'), [False]):
result = snv.qualifiers['filters']['ref_not_in_list'][None]
assert result == expected
def test_high_variable_region_filter():
'It test high_variable_region_filter'
snv1 = SeqFeature(type='snv', location=FeatureLocation(1, 1),
qualifiers={})
snv2 = SeqFeature(type='snv', location=FeatureLocation(4, 4),
qualifiers={})
snv3 = SeqFeature(type='snv', location=FeatureLocation(6, 6),
qualifiers={})
seq_str = 'AATATA'
seq = SeqWithQuality(seq=Seq(seq_str), qual=[30] * len(seq_str),
features=[snv1, snv2, snv3])
max_variability = 0.4
filter_ = create_high_variable_region_filter(max_variability)
filter_(seq)
threshold = (max_variability, None)
for snv, expected in zip(seq.get_features(kind='snv'),
[True, True, True]):
result = snv.qualifiers['filters']['high_variable_reg'][threshold]
assert result == expected
max_variability = 0.6
filter_ = create_high_variable_region_filter(max_variability)
filter_(seq)
filter_(seq)
threshold = (max_variability, None)
for snv, expected in zip(seq.get_features(kind='snv'),
[False, False, False]):
result = snv.qualifiers['filters']['high_variable_reg'][threshold]
assert result == expected
max_variability = 0.25
window = 6
threshold = (max_variability, window)
filter_ = create_high_variable_region_filter(max_variability,
window=window)
filter_(seq)
for snv, expected in zip(seq.get_features(kind='snv'),
[False, True, False]):
result = snv.qualifiers['filters']['high_variable_reg'][threshold]
assert result == expected
def test_seq_seq():
''' We are going to check the same tests but with a BioPython seq
class object inside seq'''
sequence1 = Seq('aaaccttt')
# First we initialice the quality in the init
seq1 = SeqWithQuality(name='seq1', seq=sequence1, \
qual=[2, 4 , 1, 4, 5, 6, 12, 34])
assert seq1
# Here we add the quality after the initialization
seq2 = SeqWithQuality(name='seq2', seq=sequence1)
seq2.qual = [2, 4 , 1, 4, 5, 6, 12, 34]
assert seq2
# We check if the seq can be complemented
seq3 = seq2.complement()
assert seq3.seq == 'tttggaaa'
# Let's check the sliceability of the seq
assert seq2[0:2].seq == 'aa'
assert seq2[0:2].qual == [2, 4]
def test_close_to_intron_filter():
'We filter out the snv close to an intron'
intron = SeqFeature(location=FeatureLocation(478, 478), type='intron')
snv1 = SeqFeature(type='snv', location=FeatureLocation(100, 100),
qualifiers={})
snv2 = SeqFeature(type='snv', location=FeatureLocation(450, 450),
qualifiers={})
snv3 = SeqFeature(type='snv', location=FeatureLocation(640, 640),
qualifiers={})
snv4 = SeqFeature(type='snv', location=FeatureLocation(700, 700),
qualifiers={})
seq = SeqWithQuality(seq=Seq('A' * 1000), features=[intron, snv1, snv2,
snv3, snv4])
filter_ = create_close_to_intron_filter(distance=60)
filter_(seq)
filter_(seq)
for snv, expected in zip(seq.get_features(kind='snv'),
[False, True, False, False]):
result = snv.qualifiers['filters']['close_to_intron'][60]
assert result == expected
def test_remove_annotations():
'It test ermove annotations from seq_with quality'
seq = SeqWithQuality(Seq('actg'), qual=[30, 30, 30, 30])
seq.description = 'Description'
annotations = {'arabidopsis-orthologs':'justone',
'GOs':'GO12345',
}
snv = SeqFeature(location=FeatureLocation(4, 4), type='snv')
intron = SeqFeature(location=FeatureLocation(4, 4), type='intron')
orf = SeqFeature(location=FeatureLocation(4, 4), type='orf')
ssr = SeqFeature(location=FeatureLocation(4, 4), type='microsatellite')
features = [snv, intron, orf, ssr]
seq.annotations = annotations
seq.features = features
seq.remove_annotations('GOs')
seq.remove_annotations('orthologs')
assert seq.annotations == {}
seq.remove_annotations('snv')
seq.remove_annotations('intron')
seq.remove_annotations('microsatellite')
seq.remove_annotations('orf')
seq.remove_annotations('description')
assert seq.features == []
assert seq.description == UNKNOWN_DESCRIPTION
# remome snv filters
seq = SeqWithQuality(Seq('actg'), qual=[30, 30, 30, 30])
seq.description = 'Description'
filters = {'not_intron':True, 'puff':False}
snv = SeqFeature(location=FeatureLocation(4, 4), type='snv',
qualifiers={'alleles':'alleles',
'filters':filters})
seq.features = [snv]
seq.remove_annotations('snv_filters')
assert seq.features[0].qualifiers['filters'] == {}
assert seq.features[0].qualifiers['alleles'] == 'alleles'
def test_upper():
'It test the uppercase funtion'
seq = SeqWithQuality(Seq('actg'))
seq.upper()
assert seq.seq == 'actg'
def test_is_variable_filter():
'It tests variable filter function'
alleles = {('A', SNP): {'read_groups':{'rg1':1, 'rg2':2, 'rg4':2}},
('T', INVARIANT): {'read_groups':{'rg1':1, 'rg3':2}}}
snv = SeqFeature(type='snv', location=FeatureLocation(11, 11),
qualifiers={'alleles':alleles,
'read_groups':{}})
seq = 'ATGATGATGgaaattcATGATGATGTGGGAT'
seq = SeqWithQuality(seq=Seq(seq), name='ref', features=[snv])
alleles2 = {('A', SNP): {'read_groups':{'rg1':2}}}
snv2 = SeqFeature(type='snv', location=FeatureLocation(11, 11),
qualifiers={'alleles':alleles2,
'read_groups':{}})
seq2 = 'ATGATGATGgaaattcATGATGATGTGGGAT'
seq2 = SeqWithQuality(seq=Seq(seq2), name='ref2', features=[snv2])
filters = []
parameters = []
results = []
reference_free = True
maf= None
in_all_groups = True
min_num_reads = None
min_reads_per_allele = None
kind = 'read_groups'
groups = ('rg1',)
in_union = False
params = (kind, groups, in_union, in_all_groups, reference_free, maf,
min_num_reads, min_reads_per_allele)
parameters.append(params)
filter_ = create_is_variable_filter(*params)
filters.append(filter_)
results.append(False)
kind = 'read_groups'
groups = ('rg1',)
in_union = True
params = (kind, groups, in_union, in_all_groups, reference_free, maf,
min_num_reads, min_reads_per_allele)
parameters.append(params)
filter_ = create_is_variable_filter(*params)
filters.append(filter_)
results.append(False)
kind = 'read_groups'
groups = ('rg1',)
in_union = True
min_reads_per_allele = 2
params = (kind, groups, in_union, in_all_groups, reference_free, maf,
min_num_reads, min_reads_per_allele)
parameters.append(params)
filter_ = create_is_variable_filter(*params)
filters.append(filter_)
results.append(True)
min_reads_per_allele = None
kind = 'read_groups'
groups = ('rg2', 'rg4')
in_union = True
params = (kind, groups, in_union, in_all_groups, reference_free, maf,
min_num_reads, min_reads_per_allele)
parameters.append(params)
filters.append(create_is_variable_filter(*params))
results.append(True)
kind = 'read_groups'
groups = 'fake'
in_union = True
params = (kind, (groups,), in_union, in_all_groups, reference_free, maf,
min_num_reads, min_reads_per_allele)
parameters.append(params)
filters.append(create_is_variable_filter(*params))
results.append(True)
kind = 'read_groups'
groups = ('rg2', 'rg3')
in_union = False
params = (kind, groups, in_union, in_all_groups, reference_free, maf,
min_num_reads, min_reads_per_allele)
parameters.append(params)
filters.append(create_is_variable_filter(*params))
results.append(True)
kind = 'read_groups'
groups = ('rg2', 'rg3')
in_union = True
params = (kind, groups, in_union, in_all_groups, reference_free, maf,
min_num_reads, min_reads_per_allele)
parameters.append(params)
filters.append(create_is_variable_filter(*params))
results.append(False)
kind = 'read_groups'
groups = ('rg5',)
in_union = True
params = (kind, groups, in_union, in_all_groups, reference_free, maf,
min_num_reads, min_reads_per_allele)
parameters.append(params)
filters.append(create_is_variable_filter(*params))
results.append(True)
kind = 'read_groups'
groups = ('rg2',)
in_union = True
reference_free = False
params = (kind, groups, in_union, in_all_groups, reference_free, maf,
min_num_reads, min_reads_per_allele)
parameters.append(params)
filters.append(create_is_variable_filter(*params))
results.append(False)
kind = 'read_groups'
groups = ('rg2',)
in_union = True
reference_free = True
params = (kind, groups, in_union, in_all_groups, reference_free, maf,
min_num_reads, min_reads_per_allele)
parameters.append(params)
filters.append(create_is_variable_filter(*params))
results.append(True)
for filter_ in filters:
filter_(seq)
filter_(seq2)
for params, expected in zip(parameters, results):
for snv, expected in zip(seq.get_features(kind='snv'), [expected]):
result = snv.qualifiers['filters']['is_variable'][params]
assert result == expected
for params in parameters:
for snv in seq2.get_features(kind='snv'):
assert snv.qualifiers['filters']['is_variable'][params]
def test_repr():
'It test the repr reader'
assert u'a (h)' == _cast_to_class("u'a (h)'")
assert ('adios',) == _cast_to_class("('adios',)")
assert ['arab1', 'arab2'] == _cast_to_class("['arab1', 'arab2']")
assert ('arab1', 'arab2') == _cast_to_class("('arab1', 'arab2')")
result = _cast_to_class("{1: 2}")
assert {1: 2} == result
assert {'al': {'c': 1}, 'T': 2} == _cast_to_class("{'al': {'c': 1}, 'T': 2}")
seq1 = SeqWithQuality(seq=Seq('ATCT'))
seq2 = SeqWithQuality(seq=Seq('AAAA'))
fcontent = repr(seq1) + '\n' + repr(seq2) + '\n'
fhand = StringIO.StringIO(fcontent)
seqs = list(seqs_in_file(fhand, format='repr'))
assert repr(seqs[0]) == repr(seq1)
assert repr(seqs[1]) == repr(seq2)
#with quality
seq1 = SeqWithQuality(seq=Seq('ATCT'), qual=[10, 2, 3, 4])
fcontent = repr(seq1) + '\n'
fhand = StringIO.StringIO(fcontent)
seqs = list(seqs_in_file(fhand, format='repr'))
assert repr(seqs[0]) == repr(seq1)
#a seq with features
seq1 = SeqWithQuality(seq=Seq('GAAAAGATGTG', SingleLetterAlphabet()),
id='seq', name='seq', description='', dbxrefs=[],
features=[SeqFeature(FeatureLocation(ExactPosition(478),
ExactPosition(478)),
type='intron',
qualifiers={'db': 'tomato'} ),
SeqFeature(FeatureLocation(ExactPosition(572),
ExactPosition(572)),
type='intron',
qualifiers={'db': 'tomato'} )],
annotations={}, qual=None)
fcontent = repr(seq1) + '\n'
fhand = StringIO.StringIO(fcontent)
seq0 = list(seqs_in_file(fhand, format='repr'))[0]
assert seq0.seq == seq1.seq
assert seq0.qual == seq1.qual
assert seq0.description == seq1.description
assert seq0.annotations == seq1.annotations
feat0 = seq0.features[0]
feat1 = seq1.features[0]
assert feat0.type == feat1.type
assert feat0.qualifiers == feat1.qualifiers
assert str(feat0.location) == str(feat1.location)
#some more qualifiers
fhand = tempfile.NamedTemporaryFile(suffix='.repr')
seq1 = SeqWithQuality(id='seqid', name='seqname',
description='seqdescription', seq=Seq('ATGAT'))
seq1.letter_annotations["phred_quality"] = [40, 40, 38, 30, 30]
seq1.annotations['source'] = 'ara1'
seqfeature = SeqFeature(location=FeatureLocation(5, 8),
type='orthologs',
qualifiers={'arabidposis':['arab1', 'arab2']})
seq1.features.append(seqfeature)
fcontent = repr(seq1) + '\n'
fhand = StringIO.StringIO(fcontent)
seq0 = list(seqs_in_file(fhand, format='repr'))[0]
assert seq0.seq == seq1.seq
assert seq0.qual == seq1.qual
assert seq0.description == seq1.description
assert seq0.annotations == seq1.annotations
feat0 = seq0.features[0]
feat1 = seq1.features[0]
assert feat0.type == feat1.type
assert feat0.qualifiers == feat1.qualifiers
assert str(feat0.location) == str(feat1.location)
#with snps
repr_ = "SeqWithQuality(seq=Seq('GGGGATTTG', Alphabet()), features=[SeqFeature(FeatureLocation(ExactPosition(213),ExactPosition(213)), type='snv', qualifiers={'alleles': {('C', 3): {'read_groups': ['group1+454', 'group1+454', 'group1+454'], 'qualities': [44.0, 44.0, 44.0], 'libraries': ['group1', 'group1', 'group1'], 'read_names': ['seq1', 'seq4', 'seq7'], 'orientations': [True, True, True], 'samples': ['group1+454', 'group1+454', 'group1+454'], 'quality': 66.0, 'mapping_qualities': [149, 149, 149]}, ('T', 0): {'read_groups': ['group1+454', 'group1+454', 'group1+454', 'group1+454', 'group1+454', 'group1+454'], 'qualities': [44.0, 44.0, 44.0, 44.0, 44.0, 44.0], 'libraries': ['group1', 'group1', 'group1', 'group1', 'group1', 'group1'], 'read_names': ['seq2', 'seq3', 'seq5', 'seq6', 'seq8', 'seq9'], 'orientations': [True, True, True, True, True, True], 'samples': ['group1+454', 'group1+454', 'group1+454', 'group1+454', 'group1+454', 'group1+454'], 'quality': 66.0, 'mapping_qualities': [28, 28, 28, 28, 28, 28]}}, 'reference_allele': 'C'} )])\n"
alleles = {('C', 3):
{'read_groups': ['group1+454', 'group1+454', 'group1+454'],
'qualities': [44.0, 44.0, 44.0],
'libraries': ['group1', 'group1', 'group1'],
'read_names': ['seq1', 'seq4', 'seq7'],
'orientations': [True, True, True],
'samples': ['group1+454', 'group1+454', 'group1+454'],
'quality': 66.0, 'mapping_qualities': [149, 149, 149]},
('T', 0):
{'read_groups': ['group1+454', 'group1+454', 'group1+454',
'group1+454', 'group1+454', 'group1+454'],
'qualities': [44.0, 44.0, 44.0, 44.0, 44.0, 44.0],
'libraries': ['group1', 'group1', 'group1', 'group1',
'group1', 'group1'],
'read_names': ['seq2', 'seq3', 'seq5', 'seq6', 'seq8',
'seq9'],
'orientations': [True, True, True, True, True, True],
'samples': ['group1+454', 'group1+454', 'group1+454',
'group1+454', 'group1+454', 'group1+454'],
'quality': 66.0,
'mapping_qualities': [28, 28, 28, 28, 28, 28]}
}
fcontent = repr_
fhand = StringIO.StringIO(fcontent)
seq0 = list(seqs_in_file(fhand, format='repr'))[0]
alleles0 = seq0.features[0].qualifiers['alleles']
assert alleles == alleles0
