def test_add_call_to_variant(self, probs, expected):
raw_variant = variants_pb2.Variant(
reference_name=expected.reference_name,
reference_bases=expected.reference_bases,
alternate_bases=expected.alternate_bases,
start=expected.start,
end=expected.end,
calls=[variants_pb2.VariantCall(call_set_name=_DEFAULT_SAMPLE_NAME)])
variant = postprocess_variants.add_call_to_variant(
variant=raw_variant,
predictions=probs,
sample_name=_DEFAULT_SAMPLE_NAME)
self.assertEqual(variant.reference_bases, expected.reference_bases)
self.assertEqual(variant.alternate_bases, expected.alternate_bases)
self.assertEqual(variant.reference_name, expected.reference_name)
self.assertEqual(variant.start, expected.start)
self.assertEqual(variant.end, expected.end)
self.assertAlmostEquals(variant.quality, expected.quality, places=6)
self.assertEqual(variant.filter, expected.filter)
self.assertEqual(len(variant.calls), 1)
self.assertEqual(len(expected.calls), 1)
self.assertEqual(variant.calls[0].genotype, expected.calls[0].genotype)
self.assertEqual(variant.calls[0].info['GQ'], expected.calls[0].info['GQ'])
for gl, expected_gl in zip(variant.calls[0].genotype_likelihood,
expected.calls[0].genotype_likelihood):
self.assertAlmostEquals(gl, expected_gl, places=6)
def test_add_call_to_variant(self, probs, expected):
raw_variant = variants_pb2.Variant(
reference_name=expected.reference_name,
reference_bases=expected.reference_bases,
alternate_bases=expected.alternate_bases,
start=expected.start,
end=expected.end,
calls=[variants_pb2.VariantCall(call_set_name=_DEFAULT_SAMPLE_NAME)])
variant = postprocess_variants.add_call_to_variant(
variant=raw_variant,
predictions=probs,
sample_name=_DEFAULT_SAMPLE_NAME)
self.assertEqual(variant.reference_bases, expected.reference_bases)
self.assertEqual(variant.alternate_bases, expected.alternate_bases)
self.assertEqual(variant.reference_name, expected.reference_name)
self.assertEqual(variant.start, expected.start)
self.assertEqual(variant.end, expected.end)
self.assertAlmostEquals(variant.quality, expected.quality, places=6)
self.assertEqual(variant.filter, expected.filter)
self.assertEqual(len(variant.calls), 1)
self.assertEqual(len(expected.calls), 1)
self.assertEqual(variant.calls[0].genotype, expected.calls[0].genotype)
self.assertEqual(variant.calls[0].info['GQ'], expected.calls[0].info['GQ'])
for gl, expected_gl in zip(variant.calls[0].genotype_likelihood,
expected.calls[0].genotype_likelihood):
self.assertAlmostEquals(gl, expected_gl, places=6)
def test_triallelic_genotype_in_add_call_to_variant(
self, highest_prob_position, expected_best_genotype):
"""Ensures the order of GLs are interpreted correctly for triallelics."""
raw_variant = _create_variant_with_alleles(ref='CACA', alts=['C', 'A'])
# Create a probability with 6 elements, one of them 0.995 (best genotype),
# and the rest 0.001.
probs = [0.001] * 6
assert 0 <= highest_prob_position <= len(probs)
probs[highest_prob_position] = 0.995
variant = postprocess_variants.add_call_to_variant(
variant=raw_variant,
predictions=probs,
sample_name=_DEFAULT_SAMPLE_NAME)
self.assertEqual(variant.calls[0].genotype, expected_best_genotype)
def test_triallelic_genotype_in_add_call_to_variant(
self, highest_prob_position, expected_best_genotype):
"""Ensures the order of GLs are interpreted correctly for triallelics."""
raw_variant = _create_variant_with_alleles(ref='CACA', alts=['C', 'A'])
# Create a probability with 6 elements, one of them 0.995 (best genotype),
# and the rest 0.001.
probs = [0.001] * 6
assert 0 <= highest_prob_position <= len(probs)
probs[highest_prob_position] = 0.995
variant = postprocess_variants.add_call_to_variant(
variant=raw_variant,
predictions=probs,
sample_name=_DEFAULT_SAMPLE_NAME)
self.assertEqual(variant.calls[0].genotype, expected_best_genotype)