def test_variant():
"""
Test the variant class
"""
variant = setup_variant()
assert variant.document_id == 'institute_genelist_caseid_variantid'
assert variant.variant_id == generate_md5_key('1_132_A_C'.split('_'))
assert variant.manual_rank == 5
assert variant.manual_rank_level == 'high'
def test_variant():
"""
Test the variant class
"""
variant = setup_variant()
assert variant.document_id == 'institute_genelist_caseid_variantid'
assert variant.variant_id == generate_md5_key('1_132_A_C'.split('_'))
assert variant.manual_rank == 5
assert variant.manual_rank_level == 'high'
def setup_variant(**kwargs):
"""
Setup a Variant object
"""
variant_id = kwargs.get('variant_id', '1_132_A_C')
variant = Variant(
document_id=kwargs.get('document_id',
'institute_genelist_caseid_variantid'),
variant_id=generate_md5_key(variant_id.split('_')),
display_name=variant_id,
variant_type=kwargs.get('document_id', 'clinical'),
case_id=kwargs.get('case_id', 'institute1_1'),
chromosome=kwargs.get('chromosome', '1'),
position=kwargs.get('position', 132),
reference=kwargs.get('reference', 'A'),
alternative=kwargs.get('alternative', 'C'),
rank_score=kwargs.get('rank_score', 19),
variant_rank=kwargs.get('variant_rank', 1),
quality=kwargs.get('quality', 88),
filters=kwargs.get('filters', ['PASS']),
institute=kwargs.get('institute', setup_institute()),
samples=kwargs.get('samples', []),
genetic_models=kwargs.get('genetic_models', ['AD', 'AD_dn']),
compounds=kwargs.get('compounds', []),
genes=kwargs.get('genes', []),
db_snp_ids=kwargs.get('db_snp_ids', ['rs0001']),
# Gene ids:
hgnc_symbols=kwargs.get('hgnc_symbols', ['ADK']),
ensembl_gene_ids=kwargs.get('ensembl_gene_ids', ['ENSG00000156110']),
# Frequencies:
thousand_genomes_frequency=kwargs.get('thousand_genomes_frequency',
0.001),
exac_frequency=kwargs.get('thousand_genomes_frequency', 0.002),
local_frequency=kwargs.get('local_frequency', None),
# Predicted deleteriousness:
cadd_score=kwargs.get('cadd_score', 22),
clnsig=kwargs.get('clnsig', 1),
phast_conservation=kwargs.get('phast_conservation', []),
gerp_conservation=kwargs.get('gerp_conservation', []),
phylop_conservation=kwargs.get('phylop_conservation', []),
# Database options:
gene_lists=kwargs.get('gene_lists', ['gene_list_1', 'gene_list_2']),
expected_inheritance=kwargs.get('expected_inheritance', ['AR']),
manual_rank=kwargs.get('manual_rank', 5),
acmg_evaluation=kwargs.get('acmg_evaluation', None))
return variant
def setup_variant(**kwargs):
"""
Setup a Variant object
"""
variant_id = kwargs.get('variant_id', '1_132_A_C')
variant = Variant(
document_id = kwargs.get('document_id', 'institute_genelist_caseid_variantid'),
variant_id = generate_md5_key(variant_id.split('_')),
display_name = variant_id,
variant_type = kwargs.get('document_id', 'clinical'),
case_id = kwargs.get('case_id', 'institute1_1'),
chromosome = kwargs.get('chromosome', '1'),
position = kwargs.get('position', 132),
reference = kwargs.get('reference', 'A'),
alternative = kwargs.get('alternative', 'C'),
rank_score = kwargs.get('rank_score', 19),
variant_rank = kwargs.get('variant_rank', 1),
quality = kwargs.get('quality', 88),
filters = kwargs.get('filters', ['PASS']),
institute = kwargs.get('institute', setup_institute()),
samples = kwargs.get('samples', []),
genetic_models = kwargs.get('genetic_models', ['AD', 'AD_dn']),
compounds = kwargs.get('compounds', []),
genes = kwargs.get('genes', []),
db_snp_ids = kwargs.get('db_snp_ids', ['rs0001']),
# Gene ids:
hgnc_symbols = kwargs.get('hgnc_symbols', ['ADK']),
ensembl_gene_ids = kwargs.get('ensembl_gene_ids', ['ENSG00000156110']),
# Frequencies:
thousand_genomes_frequency = kwargs.get('thousand_genomes_frequency', 0.001),
exac_frequency = kwargs.get('thousand_genomes_frequency', 0.002),
local_frequency = kwargs.get('local_frequency', None),
# Predicted deleteriousness:
cadd_score = kwargs.get('cadd_score', 22),
clnsig = kwargs.get('clnsig', 1),
phast_conservation = kwargs.get('phast_conservation', []),
gerp_conservation = kwargs.get('gerp_conservation', []),
phylop_conservation = kwargs.get('phylop_conservation', []),
# Database options:
gene_lists = kwargs.get('gene_lists', ['gene_list_1', 'gene_list_2']),
expected_inheritance = kwargs.get('expected_inheritance', ['AR']),
manual_rank = kwargs.get('manual_rank', 5),
acmg_evaluation = kwargs.get('acmg_evaluation', None)
)
return variant
