def filter_by_maf_by_allele_count(
variations,
max_allowable_maf=None,
min_allowable_maf=None,
filter_id='filter_by_maf_by_allele_count',
min_num_genotypes=MIN_NUM_GENOTYPES_FOR_POP_STAT,
calc_histogram=False,
n_bins=DEF_NUM_BINS,
limits=None):
mafs = calc_maf_by_allele_count(variations,
min_num_genotypes=min_num_genotypes)
# print(compute(mafs))
result = _select_vars(variations, mafs, min_allowable_maf,
max_allowable_maf)
if calc_histogram:
if limits is None:
limits = (0, 1)
counts, bin_edges = va.histogram(mafs, n_bins=n_bins, limits=limits)
result[FLT_STATS][COUNT] = counts
result[FLT_STATS][BIN_EDGES] = bin_edges
limits = []
if min_allowable_maf is not None:
limits.append(min_allowable_maf)
if max_allowable_maf is not None:
limits.append(max_allowable_maf)
result[FLT_STATS]['limits'] = limits
return {
FLT_VARS: result[FLT_VARS],
FLT_ID: filter_id,
FLT_STATS: result[FLT_STATS]
}
def test_calc_maf_by_allele_count_in_memory(self):
variations = Variations(samples=np.array(['aa', 'bb']))
variations[GT_FIELD] = np.array([[[-1, 1], [2, 1]], [[-1, -1], [-1,
2]],
[[1, -1], [1, 1]]])
variations[RO_FIELD] = np.array([[-1, 8], [-1, -1], [6, 4]])
variations[AO_FIELD] = np.array([[[1, 4], [2, 1]], [[-1, -1], [3, 3]],
[[1, 4], [5, 1]]])
result = calc_maf_by_allele_count(variations, min_num_genotypes=0)
expected = [0.5, 0.5, 0.47619048]
for a, b in zip(result, expected):
self.assertAlmostEqual(a, b, places=2)
def test_calc_maf_by_allele_count(self):
variations = Variations(samples=da.array(['aa', 'bb']))
variations[GT_FIELD] = da.from_array([[[-1, 1], [2, 1]],
[[-1, -1], [-1, 2]],
[[1, -1], [1, 1]]])
variations[RO_FIELD] = da.from_array(
np.array([[-1, 8], [-1, -1], [6, 4]]))
variations[AO_FIELD] = da.from_array(
np.array([[[1, 4], [2, 1]], [[-1, -1], [3, 3]], [[1, 4], [5, 1]]]))
# with this step we create a variation with dask arrays of unknown
# shapes
variations = remove_low_call_rate_vars(variations, 0)[FLT_VARS]
future_result = calc_maf_by_allele_count(variations,
min_num_genotypes=0)
result = compute(future_result)
expected = [0.5, 0.5, 0.47619048]
for a, b in zip(result, expected):
self.assertAlmostEqual(a, b, places=2)
def test_calc_maf_by_allele_count_empty_vars(self):
variations = _create_empty_dask_variations()
task = calc_maf_by_allele_count(variations)
result = compute(task)
self.assertEqual(result.shape, (0, ))