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_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_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_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_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_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]
