def test_oneLineage_returnsOnlyElement(self):
l1 = Lineage(major="4", minor="1.3.4")
classifier = Classifier()
sample_idx = 0
actual = classifier.call_sample_lineage([l1], sample_idx)
expected = str(l1)
assert actual == expected
def test_emptyList_returnsNone(self):
lineages = []
classifier = Classifier()
sample_idx = 0
expected = "unknown"
actual = classifier.call_sample_lineage(lineages, sample_idx, default=expected)
assert actual == expected
def test_variantRefDoesntMatchPanel_returnsFalse(self, mock_variant):
index = {
1: PanelVariant(Lineage("1"), 1, "G", "A"),
}
classifier = Classifier(index)
mock_variant.POS = 1
mock_variant.REF = "d"
mock_variant.FILTER = None
assert not classifier.is_variant_valid(mock_variant)
def test_oneLineageTooManyHets_returnsTooManyHets(self):
l1 = Lineage(major="4", minor="1.3.4")
classifier = Classifier(max_het=1)
sample_idx = 0
classifier.het_counts[sample_idx] = 5
actual = classifier.call_sample_lineage([l1], sample_idx)
expected = "too_many_hets"
assert actual == expected
def test_twoLineagesSameMajor_returnsLowestOnTree(self):
l1 = Lineage(major="4", minor="1.3.4")
l2 = Lineage(major="4", minor="8.3")
classifier = Classifier()
sample_idx = 0
actual = classifier.call_sample_lineage([l1, l2], sample_idx)
expected = str(l1)
assert actual == expected
def test_twoLineagesDiffMajor_returnsMixedDisregardMaxAlt(self):
l1 = Lineage(major="4", minor="1.3.4")
l2 = Lineage(major="5", minor="8.3")
classifier = Classifier(max_alt_lineages=5)
sample_idx = 0
actual = classifier.call_sample_lineage([l1, l2], sample_idx)
expected = "mixed"
assert actual == expected
def test_posNotInPanel_returnsFalse(self, mock_variant):
index = {
1: PanelVariant(Lineage("1"), 1, "G", "A"),
}
classifier = Classifier(index)
mock_variant.POS = 4
mock_variant.REF = "G"
mock_variant.FILTER = None
assert not classifier.is_variant_valid(mock_variant)
def test_panelVariantFailsFilter_returnsFalse(self, mock_variant):
index = {
1: PanelVariant(Lineage("1"), 1, "G", "A"),
}
classifier = Classifier(index)
mock_variant.POS = 1
mock_variant.REF = "G"
mock_variant.ALT = ["T", "A"]
mock_variant.FILTER = "FAIL"
assert not classifier.is_variant_valid(mock_variant)
def test_refLineagePosPanelRefInAlt_returnsTrue(self, mock_variant):
index = {
1: PanelVariant(Lineage("1"), 1, "G", "A"),
}
classifier = Classifier(index)
mock_variant.POS = 1
mock_variant.REF = "G"
mock_variant.ALT = ["T", "C"]
mock_variant.FILTER = None
assert not classifier.is_variant_valid(mock_variant)
def test_panelVariantAltNotInVariantAlts_returnsFalse(self, mock_variant):
index = {
1: PanelVariant(Lineage("1"), 1, "G", "A"),
}
classifier = Classifier(index)
mock_variant.POS = 1
mock_variant.REF = "G"
mock_variant.ALT = ["T", "C"]
mock_variant.FILTER = None
assert not classifier.is_variant_valid(mock_variant)
def test_mixedLineagesBelowThreshold_returnsMostCommon(self):
l1 = Lineage(major="4", minor="1.3.4")
l2 = Lineage(major="4", minor="1.3")
l3 = Lineage(major="5", minor="8.3")
classifier = Classifier(max_alt_lineages=1)
sample_idx = 0
actual = classifier.call_sample_lineage([l1, l2, l3], sample_idx)
expected = str(l1)
assert actual == expected
def test_panelVariantAltIsNotVariantRef_returnsFalse(self, mock_variant):
pos = 1692141
index = {
pos: PanelVariant(Lineage.from_str("4.10"), position=pos, ref="C", alt="T"),
}
classifier = Classifier(index, ref_lineage_position=pos)
mock_variant.POS = pos
mock_variant.REF = "A"
mock_variant.ALT = ["C"]
mock_variant.FILTER = None
assert not classifier.is_variant_valid(mock_variant)
def test_hetSampleDoesntHaveLineageVariant_returnsEmpty(self, mocked_variant):
index = {
1: PanelVariant(Lineage("1"), 1, "G", "A"),
}
classifier = Classifier(index)
mocked_variant.POS = 1
mocked_variant.REF = "G"
mocked_variant.ALT = ["T", "A", "N"]
mocked_variant.genotypes = [[-1, -1, False], [1, 3, False]]
mocked_variant.format.side_effect = KeyError
actual = classifier.samples_with_lineage_variant(mocked_variant)
expected = []
assert actual == expected
def test_allSamplesHaveLineageVariant_returnsAllIndices(self, mocked_variant):
index = {
1: PanelVariant(Lineage("1"), 1, "G", "A"),
}
classifier = Classifier(index)
mocked_variant.POS = 1
mocked_variant.REF = "G"
mocked_variant.ALT = ["T", "A"]
mocked_variant.genotypes = [[2, -1, False], [2, 2, False]]
mocked_variant.format.side_effect = KeyError
actual = classifier.samples_with_lineage_variant(mocked_variant)
expected = [0, 1]
assert actual == expected
def test_posNotInPanel_returnsEmpty(self, mocked_variant):
index = {
4: PanelVariant(Lineage("1"), 1, "G", "A"),
}
classifier = Classifier(index)
mocked_variant.POS = 1
mocked_variant.REF = "G"
mocked_variant.ALT = ["T", "A"]
mocked_variant.genotypes = [[2, -1, False], [2, 2, False]]
mocked_variant.format.side_effect = KeyError
actual = classifier.samples_with_lineage_variant(mocked_variant)
expected = []
assert actual == expected
def test_sampleHasLineageVariantAndPassesFilter_returnsIndex(self, mocked_variant):
index = {
1: PanelVariant(Lineage("1"), 1, "G", "A"),
}
classifier = Classifier(index)
mocked_variant.POS = 1
mocked_variant.REF = "G"
mocked_variant.ALT = ["T", "A", "N"]
mocked_variant.genotypes = [[-1, -1, False], [2, 2, False]]
mocked_variant.format.return_value = ["PASS", "PASS"]
actual = classifier.samples_with_lineage_variant(mocked_variant)
expected = [1]
assert actual == expected
def test_hetSampleHasLineageVariantIncludeHetAndIncrementHetCount_returnsHetIndex(
self, mocked_variant
):
index = {
1: PanelVariant(Lineage("1"), 1, "G", "A"),
}
classifier = Classifier(index)
mocked_variant.POS = 1
mocked_variant.REF = "G"
mocked_variant.ALT = ["T", "A"]
mocked_variant.genotypes = [[-1, -1, False], [2, 0, False]]
mocked_variant.format.side_effect = KeyError
actual = classifier.samples_with_lineage_variant(mocked_variant)
expected = [1]
assert actual == expected
assert classifier.het_counts[1] == 1
def test_panelVariantAltIsVariantRefForRefLineagePos_returnsIndex(
self, mock_variant
):
pos = 1692141
index = {
pos: PanelVariant(Lineage.from_str("4.10"), position=pos, ref="C", alt="A"),
}
classifier = Classifier(index, ref_lineage_position=pos)
mock_variant.POS = pos
mock_variant.REF = "A"
mock_variant.ALT = ["C"]
mock_variant.genotypes = [[0, 0, False], [1, 1, False]]
mock_variant.format.return_value = ["PASS", "PASS"]
actual = classifier.samples_with_lineage_variant(mock_variant)
expected = [0]
assert actual == expected
