def test_serialization():
original = VariantCollection([
Variant(
1, start=10, ref="AA", alt="AAT", ensembl=77),
Variant(10, start=15, ref="A", alt="G"),
Variant(20, start=150, ref="", alt="G"),
])
original.metadata[original[0]] = {"a": "b"}
original.metadata[original[2]] = {"bar": 2}
# This causes the variants' ensembl objects to make a SQL connection,
# which makes the ensembl object non-serializable. By calling this
# method, we are checking that we don't attempt to directly serialize
# the ensembl object.
original.effects()
# Test pickling.
serialized = pickle.dumps(original)
reconstituted = pickle.loads(serialized)
eq_(original, reconstituted)
eq_(reconstituted[0], original[0])
eq_(reconstituted.metadata[original[0]], original.metadata[original[0]])
# Test json.
serialized = original.to_json()
reconstituted = VariantCollection.from_json(serialized)
eq_(original, reconstituted)
eq_(reconstituted[0], original[0])
eq_(reconstituted.metadata[original[0]], original.metadata[original[0]])
def test_variant_collection_serialization():
variant_list = [
Variant(1, start=10, ref="AA", alt="AAT"),
Variant(10, start=15, ref="A", alt="G"),
Variant(20, start=150, ref="", alt="G"),
]
original = VariantCollection(
variant_list,
source_to_metadata_dict={
"test_data":
{variant: {
"a": "b",
"bar": 2
}
for variant in variant_list}
})
# This causes the variants' ensembl objects to make a SQL connection,
# which makes the ensembl object non-serializable. By calling this
# method, we are checking that we don't attempt to directly serialize
# the ensembl object.
original.effects()
original_first_variant = original[0]
original_metadata = original.metadata
# Test pickling
reconstructed = pickle.loads(pickle.dumps(original))
eq_(original, reconstructed)
eq_(reconstructed[0], original_first_variant)
eq_(reconstructed.metadata[original_first_variant],
original_metadata[original_first_variant])
merged = original.intersection(original)
merged_reconstructed = pickle.loads(pickle.dumps(merged))
eq_(merged, merged_reconstructed)
# Test JSON serialization
variants_from_json = VariantCollection.from_json(original.to_json())
eq_(original, variants_from_json)
eq_(variants_from_json[0], original_first_variant)
# pylint: disable=no-member
eq_(variants_from_json.metadata[original_first_variant],
original_metadata[original_first_variant])
def test_variant_collection_serialization():
variant_list = [
Variant(
1, start=10, ref="AA", alt="AAT"),
Variant(10, start=15, ref="A", alt="G"),
Variant(20, start=150, ref="", alt="G"),
]
original = VariantCollection(
variant_list,
source_to_metadata_dict={
"test_data":
{variant: {"a": "b", "bar": 2} for variant in variant_list}})
# This causes the variants' ensembl objects to make a SQL connection,
# which makes the ensembl object non-serializable. By calling this
# method, we are checking that we don't attempt to directly serialize
# the ensembl object.
original.effects()
original_first_variant = original[0]
original_metadata = original.metadata
# Test pickling
reconstructed = pickle.loads(pickle.dumps(original))
eq_(original, reconstructed)
eq_(reconstructed[0], original_first_variant)
eq_(reconstructed.metadata[original_first_variant],
original_metadata[original_first_variant])
merged = original.intersection(original)
merged_reconstructed = pickle.loads(pickle.dumps(merged))
eq_(merged, merged_reconstructed)
# Test JSON serialization
variants_from_json = VariantCollection.from_json(original.to_json())
eq_(original, variants_from_json)
eq_(variants_from_json[0], original_first_variant)
# pylint: disable=no-member
eq_(variants_from_json.metadata[original_first_variant],
original_metadata[original_first_variant])
])
gene_fpkm_dict = {
"ENSG00000165841": 10.0,
"ENSG00000204007": 20.0,
"ENSG00000276490": 30.0,
}
transcript_fpkm_dict = {
"ENST00000371321": 10.0,
"ENST00000464755": 20.0,
"ENST00000371763": 30.0,
"ENST00000613244": 40.0,
}
effects = variants.effects()
empty_variants = VariantCollection([])
empty_effects = empty_variants.effects()
def test_filter_variants():
eq_(variants.filter(lambda _: True), variants)
eq_(variants.filter(lambda _: False), empty_variants)
def test_filter_effects():
eq_(effects.filter(lambda _: True), effects)
eq_(effects.filter(lambda _: False), empty_effects)
])
gene_fpkm_dict = {
"ENSG00000165841": 10.0,
"ENSG00000204007": 20.0,
"ENSG00000276490": 30.0,
}
transcript_fpkm_dict = {
"ENST00000371321": 10.0,
"ENST00000464755": 20.0,
"ENST00000371763": 30.0,
"ENST00000613244": 40.0,
}
effects = variants.effects()
empty_variants = VariantCollection([])
empty_effects = empty_variants.effects()
def test_filter_variants():
eq_(variants.filter(lambda _: True), variants)
eq_(variants.filter(lambda _: False), empty_variants)
def test_filter_effects():
eq_(effects.filter(lambda _: True), effects)
eq_(effects.filter(lambda _: False), empty_effects)
def test_filter_variants_by_gene_expression():
eq_(variants.filter_by_gene_expression(
gene_fpkm_dict, 0.0), variants)
