def test_error_non_numeric_values_in_score_column(self):
data = "{},{}\n{},{}".format(
self.HGVS_NT_COL,
self.SCORE_COL,
generate_hgvs(prefix="c"),
"I am not a number",
)
with self.assertRaises(ValueError):
MaveDataset.for_scores(StringIO(data))
def test_defines_same_variants(self):
tests = [
(
"{},{}\nc.1A>G,0.0".format(self.HGVS_NT_COL, self.SCORE_COL),
"{},count\nc.1A>G,0.0".format(self.HGVS_NT_COL),
True,
),
(
"{},{}\nc.1A>G,0.0".format(self.HGVS_NT_COL, self.SCORE_COL),
"{},count\nc.2A>G,0.0".format(self.HGVS_NT_COL),
False,
),
(
"{},{},{}\nc.1A>G,p.Ile1Val,0.0".format(
self.HGVS_NT_COL, self.HGVS_PRO_COL, self.SCORE_COL),
"{},{},count\nc.1A>G,p.Ile1Val,0.0".format(
self.HGVS_NT_COL, self.HGVS_PRO_COL),
True,
),
(
"{},{},{}\nc.1A>G,p.Ile1Val,0.0".format(
self.HGVS_NT_COL, self.HGVS_PRO_COL, self.SCORE_COL),
"{},{},count\nc.1A>G,p.Ile1Phe,0.0".format(
self.HGVS_NT_COL, self.HGVS_PRO_COL),
False,
),
# Check returns None if either dataset invalid
(
"wrong_columns,{}\nc.1A>G,0.0".format(self.SCORE_COL),
"{},count\nc.1A>G,0.0".format(self.HGVS_NT_COL),
None,
),
(
"{},{}\nc.1A>G,0.0".format(self.HGVS_NT_COL, self.SCORE_COL),
"wrong_column,count\nc.1A>G,0.0".format(),
None,
),
]
for (scores, counts, expected) in tests:
with self.subTest(msg=(scores, counts, expected)):
scores_dataset = MaveDataset.for_scores(StringIO(scores))
scores_dataset.validate()
counts_dataset = MaveDataset.for_counts(StringIO(counts))
counts_dataset.validate()
self.assertEqual(scores_dataset.match_other(counts_dataset),
expected)
def test_invalid_hgvs_in_column(self):
tests = [
(self.HGVS_PRO_COL, generate_hgvs(prefix="c")),
(self.HGVS_SPLICE_COL, generate_hgvs(prefix="g")),
(self.HGVS_NT_COL, generate_hgvs(prefix="p")),
]
for (column, variant) in tests:
with self.subTest(msg=f"{column}: {variant}"):
if column == self.HGVS_SPLICE_COL:
data = "{},{},{}\n{},{},1.0".format(
self.HGVS_NT_COL,
column,
self.SCORE_COL,
generate_hgvs(prefix="g"),
variant,
)
else:
data = "{},{}\n{},1.0".format(column, self.SCORE_COL,
variant)
dataset = MaveDataset.for_scores(StringIO(data))
dataset.validate()
self.assertFalse(dataset.is_valid)
self.assertEqual(len(dataset.errors), 1)
print(dataset.errors)
def test_to_dict(self):
hgvs_1 = generate_hgvs(prefix="c")
hgvs_2 = generate_hgvs(prefix="c")
data = "{},{},{},{}\n{},,,\n{},,,1.0".format(
self.HGVS_NT_COL,
self.HGVS_PRO_COL,
self.HGVS_SPLICE_COL,
self.SCORE_COL,
hgvs_1,
hgvs_2,
)
dataset = MaveDataset.for_scores(StringIO(data))
dataset.validate()
self.assertTrue(dataset.is_valid)
self.assertDictEqual(
dataset.to_dict(),
{
hgvs_1: {
self.HGVS_NT_COL: hgvs_1,
self.HGVS_SPLICE_COL: None,
self.HGVS_PRO_COL: None,
self.SCORE_COL: None,
},
hgvs_2: {
self.HGVS_NT_COL: hgvs_2,
self.HGVS_SPLICE_COL: None,
self.HGVS_PRO_COL: None,
self.SCORE_COL: 1.0,
},
},
)
def test_sorts_header(self):
hgvs_nt = generate_hgvs(prefix="g")
hgvs_pro = generate_hgvs(prefix="p")
hgvs_splice = generate_hgvs(prefix="c")
data = "{},{},{},{},{}\n{},{},{},{},{}".format(
self.HGVS_PRO_COL,
self.HGVS_NT_COL,
"colA",
self.SCORE_COL,
self.HGVS_SPLICE_COL,
hgvs_pro,
hgvs_nt,
"hello",
1.0,
hgvs_splice,
)
dataset = MaveDataset.for_scores(StringIO(data))
dataset.validate()
self.assertTrue(dataset.is_valid)
self.assertListEqual(
dataset.columns,
[
self.HGVS_NT_COL,
self.HGVS_SPLICE_COL,
self.HGVS_PRO_COL,
self.SCORE_COL,
"colA",
],
)
def test_does_not_split_double_quoted_variants(self):
hgvs = "c.[123A>G;124A>G]"
data = '{},{}\n"{}",1.0'.format(self.HGVS_NT_COL, self.SCORE_COL, hgvs)
dataset = MaveDataset.for_scores(StringIO(data))
dataset.validate()
self.assertTrue(dataset.is_valid)
self.assertIn(hgvs, dataset.data()[self.HGVS_NT_COL])
def test_valid_targetseq_validation_fails(self):
data = "{},{},{}\nc.1A>G,p.Ile1Val,0.5".format(self.HGVS_NT_COL,
self.HGVS_PRO_COL,
self.SCORE_COL)
dataset = MaveDataset.for_scores(StringIO(data))
dataset.validate(targetseq="ATC")
self.assertTrue(dataset.is_valid)
def test_invalid_row_hgvs_is_not_a_string(self):
data = "{},{}\n1.0,1.0".format(self.HGVS_NT_COL, self.SCORE_COL)
dataset = MaveDataset.for_scores(StringIO(data))
dataset.validate()
self.assertFalse(dataset.is_valid)
self.assertEqual(len(dataset.errors), 1)
print(dataset.errors)
def test_empty_no_variants_parsed(self):
data = "{},{}\n".format(self.HGVS_NT_COL, self.SCORE_COL)
dataset = MaveDataset.for_scores(StringIO(data))
dataset.validate()
self.assertTrue(dataset.is_empty)
self.assertFalse(dataset.is_valid)
self.assertEqual(len(dataset.errors), 1)
print(dataset.errors)
def test_invalid_missing_either_required_hgvs_column(self):
data = "{},{}\n{},{}".format(self.HGVS_SPLICE_COL, self.SCORE_COL,
generate_hgvs(prefix="c"), 1.0)
dataset = MaveDataset.for_scores(StringIO(data))
dataset.validate()
self.assertFalse(dataset.is_valid)
self.assertEqual(len(dataset.errors), 1)
print(dataset.errors)
def test_scores_missing_scores_column(self):
data = "{},{}\n{},{}".format(self.HGVS_NT_COL, "scores_rna",
generate_hgvs(prefix="g"), 1.0)
dataset = MaveDataset.for_scores(StringIO(data))
dataset.validate()
self.assertFalse(dataset.is_valid)
self.assertEqual(len(dataset.errors), 1)
print(dataset.errors)
def test_parses_numeric_column_values_into_float(self):
hgvs = generate_hgvs(prefix="c")
data = "{},{}\n{},1.0".format(self.HGVS_NT_COL, self.SCORE_COL, hgvs)
dataset = MaveDataset.for_scores(StringIO(data))
dataset.validate()
self.assertTrue(dataset.is_valid)
value = dataset.data()[self.SCORE_COL].values[0]
self.assertIsInstance(value, float)
def test_primary_column_is_pro_when_nt_is_not_defined(self):
hgvs_pro = generate_hgvs(prefix="p")
data = "{},{}\n{},1.0".format(self.HGVS_PRO_COL, self.SCORE_COL,
hgvs_pro)
dataset = MaveDataset.for_scores(StringIO(data))
dataset.validate()
self.assertTrue(dataset.is_valid)
self.assertEqual(dataset.index_column, self.HGVS_PRO_COL)
def test_invalid_zero_is_not_parsed_as_none(self):
hgvs = generate_hgvs(prefix="c")
data = "{},{}\n{},0.0".format(self.HGVS_NT_COL, self.SCORE_COL, hgvs)
dataset = MaveDataset.for_scores(StringIO(data))
dataset.validate()
self.assertTrue(dataset.is_valid)
df = dataset.data()
self.assertEqual(df[self.SCORE_COL].values[0], 0)
def test_invalid_missing_hgvs_columns(self):
data = "{},{}\n{},1.0".format("not_hgvs", self.SCORE_COL,
generate_hgvs())
dataset = MaveDataset.for_scores(StringIO(data))
dataset.validate()
self.assertFalse(dataset.is_valid)
self.assertEqual(len(dataset.errors), 1)
print(dataset.errors)
def test_invalid_splice_not_defined_when_nt_is_genomic(self):
data = "{},{}\n{},1.0".format(self.HGVS_NT_COL, self.SCORE_COL,
generate_hgvs(prefix="g"))
dataset = MaveDataset.for_scores(StringIO(data))
dataset.validate()
self.assertFalse(dataset.is_valid)
self.assertEqual(len(dataset.errors), 2)
print(dataset.errors)
def test_invalid_same_variant_defined_in_two_rows_in_hgvs_pro(self):
hgvs = generate_hgvs(prefix="p")
data = "{},{}\n{},1.0\n{},1.0".format(self.HGVS_PRO_COL, "count", hgvs,
hgvs)
dataset = MaveDataset.for_counts(StringIO(data))
dataset.validate()
self.assertFalse(dataset.is_valid)
self.assertEqual(len(dataset.errors), 1)
print(dataset.errors)
def test_invalid_same_hgvs_nt_defined_in_two_rows(self):
hgvs = generate_hgvs(prefix="c")
data = "{},{}\n{},1.0\n{},1.0".format(self.HGVS_NT_COL, self.SCORE_COL,
hgvs, hgvs)
dataset = MaveDataset.for_scores(StringIO(data))
dataset.validate()
self.assertFalse(dataset.is_valid)
self.assertEqual(len(dataset.errors), 1)
print(dataset.errors)
def test_error_missing_value_in_pro_column_when_pro_is_primary(self):
for v in null_values_list:
with self.subTest(msg=v):
data = "{},{}\n{},1.0\n{},1.0".format(
self.HGVS_PRO_COL, self.SCORE_COL,
generate_hgvs(prefix="p"), v)
dataset = MaveDataset.for_scores(StringIO(data))
dataset.validate()
self.assertFalse(dataset.is_valid)
self.assertEqual(len(dataset.errors), 1)
print(dataset.errors)
def test_invalid_target_sequence_not_a_multiple_of_3(self):
data = "{},{},{}\nc.1A>G,p.Ile1Val,0.5".format(self.HGVS_NT_COL,
self.HGVS_PRO_COL,
self.SCORE_COL)
dataset = MaveDataset.for_scores(StringIO(data))
dataset.validate(targetseq="ATCG")
self.assertFalse(dataset.is_valid)
print(dataset.errors)
self.assertEqual(dataset.n_errors, 1)
self.assertIn("multiple of 3", dataset.errors[0])
def test_invalid_targetseq_validation_fails(self):
data = "{},{},{}\nc.1A>G,p.Val1Phe,0.5".format(self.HGVS_NT_COL,
self.HGVS_PRO_COL,
self.SCORE_COL)
dataset = MaveDataset.for_scores(StringIO(data))
dataset.validate(targetseq="ATC")
self.assertFalse(dataset.is_valid)
print(dataset.errors)
self.assertEqual(dataset.n_errors, 1)
self.assertIn("p.Val1Phe", dataset.errors[0])
def test_invalid_null_values_in_header(self):
for value in null_values_list:
with self.subTest(msg=f"'{value}'"):
data = "{},{},{}\n{},1.0,1.0".format(self.HGVS_NT_COL,
self.SCORE_COL, value,
generate_hgvs())
dataset = MaveDataset.for_scores(StringIO(data))
dataset.validate()
self.assertFalse(dataset.is_valid)
self.assertEqual(len(dataset.errors), 1)
print(dataset.errors)
def test_replaces_null_with_none_in_numeric_columns(self):
hgvs_nt = generate_hgvs(prefix="c")
for c in null_values_list:
with self.subTest(msg=f"'{c}'"):
data = "{},{}\n{},{}".format(self.HGVS_NT_COL, self.SCORE_COL,
hgvs_nt, c)
dataset = MaveDataset.for_scores(StringIO(data))
dataset.validate()
self.assertTrue(dataset.is_valid)
self.assertListEqual(
list(dataset.data(serializable=True)[self.SCORE_COL]),
[None])
def test_df_indexed_by_primary_column(self):
data = "{},{},{}\n{},{},1.0".format(
self.HGVS_NT_COL,
self.HGVS_PRO_COL,
self.SCORE_COL,
generate_hgvs(prefix="c"),
generate_hgvs(prefix="p"),
)
dataset = MaveDataset.for_scores(StringIO(data))
dataset.validate()
self.assertTrue(dataset.is_valid)
assert_index_equal(dataset.data().index, dataset.index)
def test_invalid_genomic_and_transcript_mixed_in_nt_column(self):
data = "{},{}\n{},1.0\n{},2.0".format(
self.HGVS_NT_COL,
self.SCORE_COL,
generate_hgvs(prefix="g"),
generate_hgvs(prefix="c"),
)
dataset = MaveDataset.for_scores(StringIO(data))
dataset.validate()
self.assertFalse(dataset.is_valid)
self.assertEqual(len(dataset.errors), 2)
print(dataset.errors)
def test_data_method_converts_null_values_to_None(self):
hgvs = generate_hgvs()
for value in null_values_list:
with self.subTest(msg=value):
data = "{},{}\n{},{}".format(self.HGVS_NT_COL, self.SCORE_COL,
hgvs, value)
dataset = MaveDataset.for_scores(StringIO(data))
dataset.validate()
self.assertTrue(dataset.is_valid)
df = dataset.data(serializable=True)
self.assertIsNotNone(df[self.HGVS_NT_COL].values[0])
self.assertIsNone(df[self.SCORE_COL].values[0])
def test_invalid_no_additional_columns_outside_hgvs_ones(self):
data = "{},{},{}\n{},{},{}".format(
self.HGVS_NT_COL,
self.HGVS_SPLICE_COL,
self.HGVS_PRO_COL,
generate_hgvs(prefix="g"),
generate_hgvs(prefix="c"),
generate_hgvs(prefix="p"),
)
dataset = MaveDataset.for_counts(StringIO(data))
dataset.validate()
self.assertFalse(dataset.is_valid)
self.assertEqual(len(dataset.errors), 1)
print(dataset.errors)
def test_invalid_duplicates_in_index(self):
hgvs = generate_hgvs(prefix="c")
data = "{},{},{}\n{},{},1.0\n{},{},2.0".format(
self.HGVS_NT_COL,
self.HGVS_PRO_COL,
self.SCORE_COL,
hgvs,
generate_hgvs(prefix="p"),
hgvs,
generate_hgvs(prefix="p"),
)
dataset = MaveDataset.for_scores(StringIO(data))
dataset.validate()
self.assertFalse(dataset.is_valid)
self.assertEqual(len(dataset.errors), 1)
print(dataset.errors)
def test_does_not_allow_wt_and_sy(self):
wt = "_wt"
sy = "_sy"
data = "{},{},{},{}\n{},{},{},1.0".format(
self.HGVS_NT_COL,
self.HGVS_SPLICE_COL,
self.HGVS_PRO_COL,
self.SCORE_COL,
wt,
wt,
sy,
)
dataset = MaveDataset.for_scores(StringIO(data))
dataset.validate()
self.assertFalse(dataset.is_valid)
self.assertEqual(len(dataset.errors), 3)
print(dataset.errors)