def test_add_results_to_record(self):
pfams = {
'PF00015.2': FeatureLocation(0, 3),
'PF00351.1': FeatureLocation(0, 3),
'PF00015.27': FeatureLocation(3, 6)
}
fake_record = set_dummy_with_pfams(pfams)
fake_duplicate_pfam = PFAMDomain(location=FeatureLocation(6, 9),
description='DUPLICATE',
protein_start=0,
protein_end=5,
identifier="PF00015.2",
tool="test")
fake_duplicate_pfam.domain_id = 'DUPLICATE'
fake_record.add_pfam_domain(fake_duplicate_pfam)
assert fake_duplicate_pfam in fake_record.get_pfam_domains()
gos_for_fake_pfam = pfam2go.get_gos_for_pfams(fake_record)
fake_results = pfam2go.Pfam2GoResults(fake_record.id,
gos_for_fake_pfam)
fake_results.add_to_record(fake_record)
assert fake_duplicate_pfam.full_identifier == 'PF00015.2'
for pfam in fake_record.get_pfam_domains():
assert sorted(pfam.gene_ontologies.ids) == sorted(
fake_results.get_all_gos(pfam))
# make sure identical pfams (with different version numbers) all have the same gene ontologies
if pfam.identifier == "PF00015":
assert pfam.version in [2, 27]
assert sorted(pfam.gene_ontologies.ids) == sorted(
fake_results.get_all_gos(fake_duplicate_pfam))
def setUp(self):
self.config = build_config(["--cf-create-clusters",
"--cf-mean-threshold", "0.6",
"--cf-min-cds", "5",
"--cf-min-pfams", "5"], modules=[clusterfinder],
isolated=True)
update_config({"enabled_cluster_types": []})
self.record = DummyRecord(seq=Seq("A" * 2000))
for start, end, probability, pfam_id in [(10, 20, 0.1, 'PF77777'),
(30, 40, 0.3, 'PF00106'),
(50, 60, 0.4, 'PF00107'),
(60, 70, 0.7, 'PF00109'),
(70, 80, 0.98, 'PF08484'),
(90, 100, 0.8, 'PF02401'),
(100, 110, 0.32, 'PF04369'),
(110, 120, 1.0, 'PF00128'),
(130, 140, 0.2, 'PF77776'),
(500, 505, None, 'PF77775'),
(1010, 1020, 0.1, 'PF77774'),
(1030, 1040, 0.3, 'PF00106'),
(1050, 1060, 0.4, 'PF00107'),
(1060, 1070, 0.7, 'PF00109'),
(1070, 1080, 0.98, 'PF08484'),
(1090, 1100, 0.8, 'PF02401'),
(1100, 1110, 0.32, 'PF04369'),
(1110, 1120, 1.0, 'PF00128')]:
location = FeatureLocation(start, end, strand=1)
self.record.add_cds_feature(CDSFeature(location, locus_tag=str(start), translation="A"))
pfam = PFAMDomain(location, "dummy_description", protein_start=start + 1,
protein_end=end-1, identifier=pfam_id, tool="test")
pfam.domain_id = "pfam_%d" % start
pfam.probability = probability
self.record.add_pfam_domain(pfam)
def test_pfam_domain(self):
original = PFAMDomain(FeatureLocation(2, 5),
description="test",
protein_start=5,
protein_end=10,
identifier="PF00002.17",
domain="p450",
tool="toolname")
original.domain_id = "domain_id"
original.database = "db"
original.detection = "someprogram"
original.evalue = 1e-5
original.score = 5.
original.locus_tag = "locus"
original.label = "somelabel"
original.translation = "ARNDCQ"
original.gene_ontologies = GOQualifier({
'GO:0004871': 'signal transducer activity',
'GO:0007165': 'signal transduction',
'GO:0016020': 'membrane'
})
new = PFAMDomain.from_biopython(original.to_biopython()[0])
for slot in [
"tool", "domain_id", "database", "detection", "evalue",
"score", "locus_tag", "label", "translation", "domain",
"protein_start", "protein_end", "identifier", "version"
]:
assert getattr(original, slot) == getattr(new, slot)
assert original.gene_ontologies.go_entries == new.gene_ontologies.go_entries
assert original.full_identifier == new.full_identifier
def set_dummy_with_pfams(pfam_ids: Dict[str, FeatureLocation]) -> DummyRecord:
pfam_domains = []
for pfam_id, pfam_location in pfam_ids.items():
pfam_domain = PFAMDomain(location=pfam_location,
description='FAKE',
protein_start=0,
protein_end=5,
identifier=pfam_id,
tool="test")
pfam_domain.domain_id = '%s.%d.%d' % (pfam_id, pfam_location.start,
pfam_location.end)
pfam_domains.append(pfam_domain)
return DummyRecord(features=pfam_domains)
def add_to_record(self, record: Record) -> None:
db_version = pfamdb.get_db_version_from_path(self.database)
for i, hit in enumerate(self.hits):
protein_location = FeatureLocation(hit["protein_start"], hit["protein_end"])
pfam_feature = PFAMDomain(location_from_string(hit["location"]),
description=hit["description"], protein_location=protein_location,
identifier=hit["identifier"], tool=self.tool, locus_tag=hit["locus_tag"])
for key in ["label", "locus_tag", "domain", "evalue",
"score", "translation"]:
setattr(pfam_feature, key, hit[key])
pfam_feature.database = db_version
pfam_feature.detection = "hmmscan"
pfam_feature.domain_id = "{}_{}_{:04d}".format(self.tool, pfam_feature.locus_tag, i + 1)
record.add_pfam_domain(pfam_feature)
def test_blank_records(self):
blank_no_pfams = DummyRecord()
blank_no_ids = Record(Seq("ATGTTATGAGGGTCATAACAT", generic_dna))
fake_pfam_location = FeatureLocation(0, 12)
fake_pfam = PFAMDomain(location=fake_pfam_location,
description='MCPsignal',
protein_start=0,
protein_end=5,
identifier="PF00000",
tool="test")
fake_pfam.domain_id = 'BLANK'
blank_no_ids.add_pfam_domain(fake_pfam)
assert not pfam2go.get_gos_for_pfams(blank_no_pfams)
assert not pfam2go.get_gos_for_pfams(blank_no_ids)
def add_to_record(self, record: Record) -> None:
""" Adds the hits as PFAMDomains to the given record """
db_version = pfamdb.get_db_version_from_path(self.database)
for i, hit in enumerate(self.hits):
protein_location = FeatureLocation(hit.protein_start, hit.protein_end)
pfam_feature = PFAMDomain(location_from_string(hit.location),
description=hit.description, protein_location=protein_location,
identifier=hit.identifier, tool=self.tool, locus_tag=hit.locus_tag)
for key in ["label", "locus_tag", "domain", "evalue",
"score", "translation"]:
setattr(pfam_feature, key, getattr(hit, key))
pfam_feature.database = db_version
pfam_feature.detection = "hmmscan"
pfam_feature.domain_id = "{}_{}_{:04d}".format(self.tool, pfam_feature.locus_tag, i + 1)
record.add_pfam_domain(pfam_feature)