def scan_for_functions(cds_features: List[CDSFeature], database: str,
hmmscan_opts: Optional[List[str]] = None) -> Dict[str, HMMResult]:
""" Finds possible classifications for the provided genes.
Arguments:
cds_features: a list of CDSFeatures to classify
database: the path to the database to check
hmmscan_opts: a list of extra options to provide to hmmscan
Returns:
a dictionary mapping CDS name to a list of HMMResult instances of
classifications
"""
search_fasta = fasta.get_fasta_from_features(cds_features)
results = subprocessing.run_hmmscan(database, search_fasta, hmmscan_opts)
hmm_lengths = utils.get_hmm_lengths(database)
hmm_results = refine_hmmscan_results(results, hmm_lengths)
best_hits = {} # type: Dict[str, HMMResult]
for cds in cds_features:
cds_name = cds.get_name()
hits = hmm_results.get(cds_name)
if not hits:
continue
best_hits[cds_name] = hits[0]
return best_hits
def find_ks_domains(fasta: str) -> Dict[str, List[HMMResult]]:
""" Analyse KS domains & PKS/NRPS protein domain composition to detect NRPS/PKS types
Arguments:
fasta: a group of features in fasta format
Returns:
a dictionary mapping feature name to a list of KS domain results for that feature
"""
opts = ["--cut_tc"]
ks_file = path.get_full_path(__file__, "data", "ksdomains.hmm")
lengths = utils.get_hmm_lengths(ks_file)
domains = subprocessing.run_hmmscan(ks_file, fasta, opts)
return refine_hmmscan_results(domains, lengths, neighbour_mode=True)
def find_ab_motifs(fasta: str) -> Dict[str, List[HMMResult]]:
""" Analyse for abMotifs
Arguments:
fasta: a group of features in fasta format
Returns:
a dictionary mapping feature name to a list of motif results for that feature
"""
opts = ["-E", "0.25"]
motif_file = path.get_full_path(__file__, "data", "abmotifs.hmm")
abmotif_results = subprocessing.run_hmmscan(motif_file, fasta, opts)
lengths = utils.get_hmm_lengths(motif_file)
return refine_hmmscan_results(abmotif_results, lengths, neighbour_mode=True)
def run_t2pks_hmmscan(cluster: Cluster) -> Dict[str, List[HMMResult]]:
""" Runs hmmscan for type II PKS proteins on coding sequences in cluster
Arguments:
cluster: Cluster on which the type II PKS hmmscan shall be run
Returns:
a dictionary of key: cds and value: list of HMMResults, for hmmscan results of the cluster
"""
cluster_fasta = fasta.get_fasta_from_features(cluster.cds_children)
hmm_file = path.get_full_path(__file__, "data", "t2pks.hmm")
hmm_results = subprocessing.run_hmmscan(hmm_file,
cluster_fasta,
opts=['--cut_tc'])
hmm_lengths = get_hmm_lengths(hmm_file)
return refine_hmmscan_results(hmm_results, hmm_lengths)
def find_domains(fasta: str, record: Record) -> Dict[str, List[HMMResult]]:
""" Analyse for C/A/PCP/E/KS/AT/ATd/DH/KR/ER/ACP/TE/TD/COM/Docking/MT/CAL domains
Arguments:
fasta: a group of features in fasta format
record: the Record that contains all the features
Returns:
a dictionary mapping feature name to a list of domain results for that feature
"""
opts = ["--cut_tc"]
nrpspks_file = path.get_full_path(__file__, "data", "nrpspksdomains.hmm")
nrpspksdomain_results = subprocessing.run_hmmscan(nrpspks_file, fasta, opts)
lengths = utils.get_hmm_lengths(nrpspks_file)
domains = refine_hmmscan_results(nrpspksdomain_results, lengths, neighbour_mode=True)
return filter_nonterminal_docking_domains(record, domains)
def run_t2pks_hmmscan(
cds_features: Iterable[CDSFeature]) -> Dict[str, List[HMMResult]]:
""" Runs hmmscan for type II PKS proteins on the given CDSFeatures
Arguments:
cluster: Protocluster on which to run the type II PKS hmmscan
Returns:
a dictionary of key: cds and value: list of HMMResults, for hmmscan results of the cluster
"""
cluster_fasta = fasta.get_fasta_from_features(cds_features)
hmm_file = path.get_full_path(__file__, "data", "t2pks.hmm")
hmm_results = subprocessing.run_hmmscan(hmm_file,
cluster_fasta,
opts=['--cut_tc'])
hmm_lengths = get_hmm_lengths(hmm_file)
return refine_hmmscan_results(hmm_results, hmm_lengths)
def classify_genes(
cds_features: List[CDSFeature]) -> Dict[str, List[HMMResult]]:
""" Finds possible classifications for the provided genes.
Arguments:
cds_features: a list of CDSFeatures to classify
Returns:
a dictionary mapping CDS name to a list of HMMResult instances of
classifications
"""
smcogs_fasta = fasta.get_fasta_from_features(cds_features)
smcogs_opts = ["-E", "1E-6"]
hmm_file = path.get_full_path(__file__, "data", "smcogs.hmm")
smcogs_results = subprocessing.run_hmmscan(hmm_file, smcogs_fasta,
smcogs_opts)
hmm_lengths = utils.get_hmm_lengths(hmm_file)
return refine_hmmscan_results(smcogs_results, hmm_lengths)
