def test_query_gene_function_mga_metap(db: Session):
sample1 = fakes.BiosampleFactory(id="sample1")
fakes.BiosampleFactory(id="sample2")
gene_functions = [
fakes.MGAGeneFunction(function__id=f"function{i}") for i in range(10)
]
fakes.MetagenomeAnnotationFactory(id="mga1",
gene_functions=gene_functions,
omics_processing__biosample=sample1)
metap = fakes.MetaproteomicAnalysisFactory(id="metap1")
peptide = fakes.MetaproteomicPeptideFactory(
metaproteomic_analysis=metap, best_protein_object=gene_functions[2])
fakes.PeptideMGAGeneFunctionFactory(mga_gene_function=gene_functions[1],
metaproteomic_peptide=peptide)
db.commit()
models.MGAGeneFunctionAggregation.populate(db)
models.MetaPGeneFunctionAggregation.populate(db)
db.commit()
q = query.MetagenomeAnnotationQuerySchema(conditions=[{
"table": "gene_function",
"field": "id",
"value": "function1",
}], )
assert {r.id for r in q.execute(db)} == {"mga1"}
q = query.MetagenomeAnnotationQuerySchema(conditions=[{
"table": "gene_function",
"field": "id",
"value": "invalid",
}], )
assert {r.id for r in q.execute(db)} == set()
q1 = query.MetaproteomicAnalysisQuerySchema(conditions=[{
"table":
"gene_function",
"field":
"id",
"value":
"function1",
}], )
assert {r.id for r in q1.execute(db)} == {"metap1"}
q1 = query.MetaproteomicAnalysisQuerySchema(conditions=[{
"table": "gene_function",
"field": "id",
"value": "invalid",
}], )
assert {r.id for r in q1.execute(db)} == set()
def binned_facet_metaproteomic_analysis(
db: Session,
attribute: str,
conditions: List[query.ConditionSchema],
**kwargs,
) -> query.BinnedFacetResponse:
bins, facets = query.MetaproteomicAnalysisQuerySchema(
conditions=conditions).binned_facet(db, attribute, **kwargs)
return query.BinnedFacetResponse(bins=bins, facets=facets)
def test_basic_query(db: Session, table):
tests: Dict[str, Tuple[fakes.AnnotatedFactory, query.BaseQuerySchema]] = {
"study": (fakes.StudyFactory(), query.StudyQuerySchema()),
"omics_processing":
(fakes.OmicsProcessingFactory(), query.OmicsProcessingQuerySchema()),
"biosample": (fakes.BiosampleFactory(), query.BiosampleQuerySchema()),
"reads_qc": (fakes.ReadsQCFactory(), query.ReadsQCQuerySchema()),
"metagenome_assembly": (
fakes.MetagenomeAssemblyFactory(),
query.MetagenomeAssemblyQuerySchema(),
),
"metagenome_annotation": (
fakes.MetagenomeAnnotationFactory(),
query.MetagenomeAnnotationQuerySchema(),
),
"metaproteomic_analysis": (
fakes.MetaproteomicAnalysisFactory(),
query.MetaproteomicAnalysisQuerySchema(),
),
}
db.commit()
q = tests[table][1].execute(db)
assert tests[table][0].id in {r.id for r in q.all()}
def facet_metaproteomic_analysis(
db: Session, attribute: str,
conditions: List[query.ConditionSchema]) -> query.FacetResponse:
facets = query.MetaproteomicAnalysisQuerySchema(
conditions=conditions).facet(db, attribute)
return query.FacetResponse(facets=facets)
def search_metaproteomic_analysis(
db: Session, conditions: List[query.ConditionSchema]) -> Query:
return query.MetaproteomicAnalysisQuerySchema(
conditions=conditions).execute(db)