def from_json(data: Dict[str, Any]) -> "CDSResult":
""" Reconstruct from a JSON representation """
domain_hmms = [HMMResult.from_json(hmm) for hmm in data["domain_hmms"]]
motif_hmms = [HMMResult.from_json(hmm) for hmm in data["motif_hmms"]]
modules = [Module.from_json(module) for module in data["modules"]]
return CDSResult(domain_hmms, motif_hmms, data["type"], modules,
data["ks_subtypes"])
def test_results_reconstruction(self):
def check_results(results):
assert results.record_id == "rec_id"
assert results.tool == "toolname"
assert isinstance(results.best_hits["cds1"], HMMResult)
assert results.best_hits["cds1"].hit_id == 'desc1'
assert results.best_hits["cds2"].bitscore == 20
assert results.function_mapping["cds2"] == GeneFunction.REGULATORY
hits = {
"cds1": HMMResult("desc1", 0, 100, 2.3e-126, 416),
"cds2": HMMResult("desc2", 5, 60, 3e-16, 20),
}
mapping = {
"cds1": GeneFunction.TRANSPORT,
"cds2": GeneFunction.REGULATORY,
}
results = self.res_class("rec_id",
"toolname",
best_hits=hits,
function_mapping=mapping)
check_results(results)
json = results.to_json()
assert json["best_hits"]["cds1"][0] == hits["cds1"].hit_id
record = DummyRecord()
record.id = "rec_id"
reconstructed = self.res_class.from_json(json, record)
check_results(reconstructed)
def setUp(self):
self.res_class = genefunctions.core.FunctionResults
hits = {"cds1": HMMResult("desc1", 0, 100, 2.3e-126, 416),
"cds2": HMMResult("desc2", 5, 60, 3e-16, 20),
}
mapping = {"cds1": GeneFunction.TRANSPORT,
"cds2": GeneFunction.REGULATORY,
}
self.record = DummyRecord()
self.record.id = "rec_id"
self.results = self.res_class(self.record.id, "toolname", best_hits=hits,
function_mapping=mapping)
def classify(
record_id: str,
cds_features: List[CDSFeature], # an API, so hide unused warning
options: ConfigType
) -> FunctionResults: # pylint: disable=unused-argument
""" Finds possible classifications for the provided CDS features.
Arguments:
cds_features: a list of CDSFeatures to classify
Returns:
a dictionary mapping CDS name to a list of HMMResult instances of
classifications
"""
hmm_file = path.get_full_path(__file__, "data", "smcogs.hmm")
hits = scan_for_functions(cds_features,
hmm_file,
hmmscan_opts=["-E", "1E-16"])
ids_to_function = build_function_mapping()
cds_name_to_function = {}
for cds_name, result in hits.items():
smcog_id = result.hit_id.split(":", 1)[0]
cds_name_to_function[cds_name] = ids_to_function[smcog_id]
hits[cds_name] = HMMResult(result.hit_id.replace("_", " "),
result.query_start, result.query_end,
result.evalue, result.bitscore)
return FunctionResults(record_id, "smcogs", hits, cds_name_to_function)
def test_biopython_compatibility(self):
qualifier = NRPSPKSQualifier(strand=1)
for pks in ["PKS_AT", "AMP-binding"]:
qualifier.add_domain(HMMResult(pks, 1, 1, 1, 1), "missing")
qualifier.add_subtype(pks + "dummy")
assert len(qualifier) == 4
for i in qualifier:
assert isinstance(i, str)
def test_counter(self):
qualifier = NRPSPKSQualifier(strand=1)
types = [("PKS_AT", "_AT"), ("PKS_KR", "_KR"), ("CAL_domain", "_CAL"),
("AMP-binding", "_A"), ("PKS_KS", "_KS"), ("ACP", "_OTHER")]
expected = set()
for pks_type, suffix in types:
domain = HMMResult(pks_type, 1, 1, 1, 1)
suffix = suffix + "%d"
for i in range(3):
qualifier.add_domain(domain, "missing")
expected.add(suffix % (i + 1))
assert len(qualifier.domains) == 3 * len(types)
assert {domain.label for domain in qualifier.domains} == expected
def test_classification_with_colon(self):
# since SMCOG id and description are stored in a string separated by :,
# ensure that descriptions containing : are properly handled
cds = helpers.DummyCDS(locus_tag="test")
record = helpers.DummyRecord(features=[cds], seq="A" * 100)
record.add_cluster(helpers.DummyCluster(0, 100))
results = SMCOGResults(record.id)
results.best_hits[cds.get_name()] = HMMResult(
"SMCOG1212:sodium:dicarboxylate_symporter", 0, 100, 2.3e-126, 416)
results.add_to_record(record)
gene_functions = cds.gene_functions.get_by_tool("smcogs")
assert len(gene_functions) == 1
assert str(gene_functions[0]).startswith(
"transport (smcogs) SMCOG1212:sodium:dicarboxylate_symporter"
" (Score: 416; E-value: 2.3e-126)")
def from_json(json: Dict[str, Any], record: Record) -> Optional["FunctionResults"]:
if json.get("schema_version") != FunctionResults.schema_version:
logging.debug("Schema version mismatch, discarding FunctionResults for tool: %s",
json.get("tool", "unknown"))
return None
if record.id != json.get("record_id"):
logging.debug("Record ID mismatch, discarding FunctionResults for tool: %s",
json.get("tool", "unknown"))
return None
hits = {}
for hit, parts in json["best_hits"].items():
hits[hit] = HMMResult(*parts)
mapping = {}
for cds_name, simple_function in json["mapping"].items():
mapping[cds_name] = GeneFunction.from_string(simple_function)
results = FunctionResults(json["record_id"], json["tool"], hits, mapping)
return results
def test_biopython_conversion(self):
qualifier = NRPSPKSQualifier(strand=1)
for pks in ["PKS_AT", "AMP-binding"]:
qualifier.add_domain(HMMResult(pks, 1, 1, 1, 1), "missing")
qualifier.add_subtype(pks + "dummy")
qualifier.type = "some type"
bio = list(qualifier)
for val in bio:
assert isinstance(val, str)
new = NRPSPKSQualifier(strand=1)
new.add_from_qualifier(bio)
assert list(qualifier) == list(new)
for bad in [["mismatching info"], ["Domain: missing info"]]:
with self.assertRaisesRegex(
ValueError, "unknown NRPS/PKS qualifier|could not match"):
new.add_from_qualifier(bad)
def run_starter_unit_blastp(
cds_hmm_hits: Dict[CDSFeature,
List[HMMResult]]) -> Dict[str, List[HMMResult]]:
""" Runs blastp on starter unit coding sequences in given cluster
Arguments:
cds_hmm_hits: HMMResults by cds from type II PKS hmmscan
Returns:
a dictionary mapping CDS name to a list of HMMresults
"""
blastp_results = []
blastp_fasta_files = set()
for cds, hmm_hits in cds_hmm_hits.items():
query_sequence = fasta.get_fasta_from_features([cds])
for hit in hmm_hits:
if hit.hit_id not in ['KSIII', 'AT', 'AMID', 'LIG']:
continue
blast_database = path.get_full_path(__file__, 'data', hit.hit_id)
blastp_results.extend(
subprocessing.run_blastp(blast_database, query_sequence))
blastp_fasta_files.add(
path.get_full_path(__file__, 'data', hit.hit_id + '.fasta'))
if not blastp_results:
return {}
fasta_lengths = {}
for fasta_file in blastp_fasta_files:
fasta_lengths.update(get_fasta_lengths(fasta_file))
results = refine_hmmscan_results(blastp_results, fasta_lengths)
for hits in results.values():
for i, hit in enumerate(hits):
if not hit.hit_id.endswith("-CoA"):
hits[i] = HMMResult(hit.hit_id + "-CoA", hit.query_start,
hit.query_end, hit.evalue, hit.bitscore)
return results
def from_json(cls, data: Dict[str, Any]) -> "Component":
""" Construct a component from a JSON representation """
subtype = data.get("subtype", "")
assert isinstance(subtype, str), subtype
return cls(HMMResult.from_json(data["domain"]), data["locus"], subtype)
def dummy_hmm(hit_id="dummy", start=1):
return HMMResult(hit_id, start, start + 40, 1e-5, 10)
def from_json(data) -> "CDSResult":
""" Reconstruct from a JSON representation """
domain_hmms = [HMMResult.from_json(hmm) for hmm in data["domain_hmms"]]
motif_hmms = [HMMResult.from_json(hmm) for hmm in data["motif_hmms"]]
return CDSResult(domain_hmms, motif_hmms, data["type"])
def setUp(self):
test_file = path.get_full_path(__file__, 'data',
'NC_003888.3.cluster011.gbk')
self.record = record_processing.parse_input_sequence(test_file)[0]
self.cluster = Cluster(FeatureLocation(0, len(self.record.seq)),
surrounding_location=FeatureLocation(
0, len(self.record.seq)),
cutoff=20,
neighbourhood_range=0,
tool="test",
product="T2PKS",
detection_rule="dummy rule")
self.record.add_cluster(self.cluster)
self.record.create_superclusters()
self.record.create_regions()
hmm_results = {
'SCO5072':
[HMMResult("KR", 1, 265, evalue=3.1e-49, bitscore=159.4)],
'SCO5079':
[HMMResult("DIMER", 4, 293, evalue=8.7e-131, bitscore=426.8)],
'SCO5080':
[HMMResult("OXY", 8, 377, evalue=2.1e-14, bitscore=44.7)],
'SCO5086':
[HMMResult("KR_C9", 0, 261, evalue=1.9e-134, bitscore=438.4)],
'SCO5087':
[HMMResult("KS", 44, 463, evalue=3.5e-234, bitscore=768.6)],
'SCO5088':
[HMMResult("CLF_7", 1, 401, evalue=1.2e-226, bitscore=743.5)],
'SCO5089': [HMMResult("ACP", 4, 86, evalue=5e-36, bitscore=114.2)],
'SCO5090':
[HMMResult("CYC_C7-C12", 1, 312, evalue=7.8e-124, bitscore=404)],
'SCO5091':
[HMMResult("CYC_C5-C14", 3, 297, evalue=4.4e-143, bitscore=467.3)],
'SCO5094':
[HMMResult("MET", 40, 155, evalue=9.8e-11, bitscore=32.7)],
'SCO5097':
[HMMResult("KR", 3, 247, evalue=3.3e-40, bitscore=129.8)],
}
mock("t2pks_analysis.run_t2pks_hmmscan", returns=hmm_results)
mock("t2pks_analysis.run_starter_unit_blastp", returns={})
def hmm_results(self):
hmm_results = {'SCO5072': [HMMResult("KR", 1, 265, evalue=3.1e-49, bitscore=159.4)],
'SCO5079': [HMMResult("DIMER", 4, 293, evalue=8.7e-131, bitscore=426.8)],
'SCO5080': [HMMResult("OXY", 8, 377, evalue=2.1e-14, bitscore=44.7)],
'SCO5086': [HMMResult("KR_C9", 0, 261, evalue=1.9e-134, bitscore=438.4)],
'SCO5087': [HMMResult("KS", 44, 463, evalue=3.5e-234, bitscore=768.6)],
'SCO5088': [HMMResult("CLF_7", 1, 401, evalue=1.2e-226, bitscore=743.5)],
'SCO5089': [HMMResult("ACP", 4, 86, evalue=5e-36, bitscore=114.2)],
'SCO5090': [HMMResult("CYC_C7-C12", 1, 312, evalue=7.8e-124, bitscore=404)],
'SCO5091': [HMMResult("CYC_C5-C14", 3, 297, evalue=4.4e-143, bitscore=467.3)],
'SCO5094': [HMMResult("MET", 40, 155, evalue=9.8e-11, bitscore=32.7)],
'SCO5097': [HMMResult("KR", 3, 247, evalue=3.3e-40, bitscore=129.8)],
}
return hmm_results
