def test_filter_chi2_gt_sample_sets(self):
variations = VariationsArrays()
gts = numpy.array([[[0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0]],
[[0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0]],
[[0, 0], [0, 0], [0, 1], [1, 1], [1, 1], [1, 1]],
[[0, 0], [0, 0], [0, 1], [1, 1], [1, 1], [1, 1]]])
variations[GT_FIELD] = gts
variations.samples = [1, 2, 3, 4, 5, 6]
samples1 = [1, 2, 3]
samples2 = [4, 5, 6]
flt = Chi2GtFreqs2SampleSetsFilter(samples1,
samples2,
min_pval=0.05,
n_bins=2,
report_selection=True)
res = flt(variations)
assert list(res[COUNTS]) == [2, 2]
assert numpy.all(res[FLT_VARS][GT_FIELD] == gts[:2, ...])
assert res[FLT_STATS][N_KEPT] == 2
assert res[FLT_STATS][TOT] == 4
assert res[FLT_STATS][N_FILTERED_OUT] == 2
assert res[SELECTED_VARS].shape
flt = Chi2GtFreqs2SampleSetsFilter(samples1,
samples2,
min_pval=0.05,
n_bins=2,
return_discarded=True)
res = flt(variations)
assert res[DISCARDED_VARS].num_variations
def test_filter_or(self):
variations = VariationsArrays()
gts = numpy.array([[[0, 0], [1, 1], [0, 1], [1, 1], [0, 0]],
[[0, 0], [0, 0], [0, 0], [0, 0], [1, 1]],
[[0, 0], [0, 0], [0, 0], [0, 0], [0, 1]],
[[0, 0], [0, 0], [0, 1], [0, 0], [1, 1]]])
variations[GT_FIELD] = gts
variations.samples = [1, 2, 3, 4, 5]
filter1 = ObsHetFilter(min_num_genotypes=0)
filter2 = ObsHetFilter(min_het=0.2, min_num_genotypes=0)
filtered = OrFilter([filter1, filter2])(variations)
assert numpy.all(filtered[FLT_VARS][GT_FIELD] == gts)
assert filtered[FLT_STATS][N_KEPT] == 4
assert filtered[FLT_STATS][TOT] == 4
assert filtered[FLT_STATS][N_FILTERED_OUT] == 0
def test_filter_or(self):
variations = VariationsArrays()
gts = numpy.array([[[0, 0], [1, 1], [0, 1], [1, 1], [0, 0]],
[[0, 0], [0, 0], [0, 0], [0, 0], [1, 1]],
[[0, 0], [0, 0], [0, 0], [0, 0], [0, 1]],
[[0, 0], [0, 0], [0, 1], [0, 0], [1, 1]]])
variations[GT_FIELD] = gts
variations.samples = [1, 2, 3, 4, 5]
filter1 = ObsHetFilter(min_num_genotypes=0)
filter2 = ObsHetFilter(min_het=0.2, min_num_genotypes=0)
filtered = OrFilter([filter1, filter2])(variations)
assert numpy.all(filtered[FLT_VARS][GT_FIELD] == gts)
assert filtered[FLT_STATS][N_KEPT] == 4
assert filtered[FLT_STATS][TOT] == 4
assert filtered[FLT_STATS][N_FILTERED_OUT] == 0
def test_filter_chi2_gt_sample_sets(self):
variations = VariationsArrays()
gts = numpy.array([[[0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0]],
[[0, 0], [0, 0], [0, 0], [0, 0], [0, 0], [0, 0]],
[[0, 0], [0, 0], [0, 1], [1, 1], [1, 1], [1, 1]],
[[0, 0], [0, 0], [0, 1], [1, 1], [1, 1], [1, 1]]])
variations[GT_FIELD] = gts
variations.samples = [1, 2, 3, 4, 5, 6]
samples1 = [1, 2, 3]
samples2 = [4, 5, 6]
flt = Chi2GtFreqs2SampleSetsFilter(samples1, samples2, min_pval=0.05,
n_bins=2, report_selection=True)
res = flt(variations)
assert list(res[COUNTS]) == [2, 2]
assert numpy.all(res[FLT_VARS][GT_FIELD] == gts[:2, ...])
assert res[FLT_STATS][N_KEPT] == 2
assert res[FLT_STATS][TOT] == 4
assert res[FLT_STATS][N_FILTERED_OUT] == 2
assert res[SELECTED_VARS].shape
flt = Chi2GtFreqs2SampleSetsFilter(samples1, samples2, min_pval=0.05,
n_bins=2, return_discarded=True)
res = flt(variations)
assert res[DISCARDED_VARS].num_variations
def test_filter_obs_het(self):
variations = VariationsArrays()
gts = numpy.array([[[0, 0], [1, 1], [0, 1], [1, 1], [0, 0]],
[[0, 0], [0, 0], [0, 0], [0, 0], [1, 1]],
[[0, 0], [0, 0], [0, 0], [0, 0], [0, 1]],
[[0, 0], [0, 0], [0, 1], [0, 0], [1, 1]]])
variations[GT_FIELD] = gts
variations.samples = [1, 2, 3, 4, 5]
filtered = ObsHetFilter(min_num_genotypes=0,
report_selection=True)(variations)
assert numpy.all(filtered[FLT_VARS][GT_FIELD] == gts)
assert filtered[FLT_STATS][N_KEPT] == 4
assert filtered[FLT_STATS][TOT] == 4
assert filtered[FLT_STATS][N_FILTERED_OUT] == 0
assert filtered[SELECTED_VARS].shape
filtered = ObsHetFilter(min_het=0.2, min_num_genotypes=0)(variations)
assert numpy.all(filtered[FLT_VARS][GT_FIELD] == gts[[0, 2, 3]])
assert filtered[FLT_STATS][N_KEPT] == 3
assert filtered[FLT_STATS][TOT] == 4
assert filtered[FLT_STATS][N_FILTERED_OUT] == 1
filtered = ObsHetFilter(min_het=0.2, min_num_genotypes=10)(variations)
assert filtered[FLT_STATS][N_KEPT] == 0
assert filtered[FLT_STATS][TOT] == 4
assert filtered[FLT_STATS][N_FILTERED_OUT] == 4
filtered = ObsHetFilter(min_het=0.2, min_num_genotypes=10,
keep_missing=True)(variations)
assert filtered[FLT_STATS][N_KEPT] == 4
assert filtered[FLT_STATS][TOT] == 4
assert filtered[FLT_STATS][N_FILTERED_OUT] == 0
return
filtered = ObsHetFilter(max_het=0.1, min_num_genotypes=0)(variations)
assert numpy.all(filtered[FLT_VARS][GT_FIELD] == gts[[1]])
filtered = ObsHetFilter(min_het=0.2, max_het=0.3,
min_num_genotypes=0)(variations)
assert numpy.all(filtered[FLT_VARS][GT_FIELD] == gts[[0, 2, 3]])
hdf5 = VariationsH5(join(TEST_DATA_DIR, 'ril.hdf5'), mode='r')
filtered = ObsHetFilter(min_het=0.6, max_het=0.9)(hdf5)
counts = Counter(filtered[FLT_VARS][GT_FIELD].flat)
assert counts == {}
filtered = ObsHetFilter(min_het=0.6, max_het=0.9, min_call_dp=5)(hdf5)
counts = Counter(filtered[FLT_VARS][GT_FIELD].flat)
assert counts == {0: 978, -1: 910, 1: 774, 2: 92}
filtered = ObsHetFilter(min_het=0.6, max_het=0.9, min_call_dp=5,
n_bins=3, range_=(0, 1))(hdf5)
counts = Counter(filtered[FLT_VARS][GT_FIELD].flat)
assert counts == {0: 978, -1: 910, 1: 774, 2: 92}
assert numpy.all(filtered[COUNTS] == [391, 14, 10])
assert numpy.all(filtered[EDGES] == [0, 1 / 3, 2 / 3, 1])
samples = hdf5.samples[:50]
filtered = ObsHetFilter(min_het=0.6, max_het=0.9, min_call_dp=5,
n_bins=3, range_=(0, 1), samples=samples)(hdf5)
counts = Counter(filtered[FLT_VARS][GT_FIELD].flat)
assert sum(filtered[COUNTS]) == sum([339, 14, 6])
def test_filter_obs_het(self):
variations = VariationsArrays()
gts = numpy.array([[[0, 0], [1, 1], [0, 1], [1, 1], [0, 0]],
[[0, 0], [0, 0], [0, 0], [0, 0], [1, 1]],
[[0, 0], [0, 0], [0, 0], [0, 0], [0, 1]],
[[0, 0], [0, 0], [0, 1], [0, 0], [1, 1]]])
variations[GT_FIELD] = gts
variations.samples = [1, 2, 3, 4, 5]
filtered = ObsHetFilter(min_num_genotypes=0,
report_selection=True)(variations)
assert numpy.all(filtered[FLT_VARS][GT_FIELD] == gts)
assert filtered[FLT_STATS][N_KEPT] == 4
assert filtered[FLT_STATS][TOT] == 4
assert filtered[FLT_STATS][N_FILTERED_OUT] == 0
assert filtered[SELECTED_VARS].shape
filtered = ObsHetFilter(min_het=0.2, min_num_genotypes=0)(variations)
assert numpy.all(filtered[FLT_VARS][GT_FIELD] == gts[[0, 2, 3]])
assert filtered[FLT_STATS][N_KEPT] == 3
assert filtered[FLT_STATS][TOT] == 4
assert filtered[FLT_STATS][N_FILTERED_OUT] == 1
filtered = ObsHetFilter(min_het=0.2, min_num_genotypes=10)(variations)
assert filtered[FLT_STATS][N_KEPT] == 0
assert filtered[FLT_STATS][TOT] == 4
assert filtered[FLT_STATS][N_FILTERED_OUT] == 4
filtered = ObsHetFilter(min_het=0.2,
min_num_genotypes=10,
keep_missing=True)(variations)
assert filtered[FLT_STATS][N_KEPT] == 4
assert filtered[FLT_STATS][TOT] == 4
assert filtered[FLT_STATS][N_FILTERED_OUT] == 0
return
filtered = ObsHetFilter(max_het=0.1, min_num_genotypes=0)(variations)
assert numpy.all(filtered[FLT_VARS][GT_FIELD] == gts[[1]])
filtered = ObsHetFilter(min_het=0.2, max_het=0.3,
min_num_genotypes=0)(variations)
assert numpy.all(filtered[FLT_VARS][GT_FIELD] == gts[[0, 2, 3]])
hdf5 = VariationsH5(join(TEST_DATA_DIR, 'ril.hdf5'), mode='r')
filtered = ObsHetFilter(min_het=0.6, max_het=0.9)(hdf5)
counts = Counter(filtered[FLT_VARS][GT_FIELD].flat)
assert counts == {}
filtered = ObsHetFilter(min_het=0.6, max_het=0.9, min_call_dp=5)(hdf5)
counts = Counter(filtered[FLT_VARS][GT_FIELD].flat)
assert counts == {0: 978, -1: 910, 1: 774, 2: 92}
filtered = ObsHetFilter(min_het=0.6,
max_het=0.9,
min_call_dp=5,
n_bins=3,
range_=(0, 1))(hdf5)
counts = Counter(filtered[FLT_VARS][GT_FIELD].flat)
assert counts == {0: 978, -1: 910, 1: 774, 2: 92}
assert numpy.all(filtered[COUNTS] == [391, 14, 10])
assert numpy.all(filtered[EDGES] == [0, 1 / 3, 2 / 3, 1])
samples = hdf5.samples[:50]
filtered = ObsHetFilter(min_het=0.6,
max_het=0.9,
min_call_dp=5,
n_bins=3,
range_=(0, 1),
samples=samples)(hdf5)
counts = Counter(filtered[FLT_VARS][GT_FIELD].flat)
assert sum(filtered[COUNTS]) == sum([339, 14, 6])
