def annotate(self):
self.annotation_file = self.describer.get_refdata_dict().get(
"sequence_1").annotation_file
self._raw_nfasta_df = pd.read_table(self.annotation_file,
sep='\t',
header=0)
mp_result = Utilities.multi_core_queue(
self._mp_parse_nfasta_header,
self._raw_nfasta_df["former_id"].values.tolist())
self._processed_nfasta_df = Utilities.merge_pd_series_list(
mp_result).sort_values("former_id")
self.nfasta_df = Utilities.left_merge(self._raw_nfasta_df,
self._processed_nfasta_df,
"former_id")
# Join 'aro_index.tsv'
aro_index_df = pd.read_table(os.path.join(self.reference_dir, "data",
"aro_index.tsv"),
sep='\t',
header=0)
aro_index_df["aro_id"] = aro_index_df["ARO Accession"].str.extract(
"ARO:(\d+)")
# 'aro_index.tsv' has more entries than 'nucleotide_fasta_protein_homolog_model.fasta' provides
self.nfasta_df = Utilities.left_merge(self.nfasta_df, aro_index_df,
"aro_id")
# Join 'aro_categories_index.tsv'
aro_categories_index_df = pd.read_table(os.path.join(
self.reference_dir, "data", "aro_categories_index.tsv"),
sep='\t',
header=0)
self.nfasta_df = Utilities.left_merge(self.nfasta_df,
aro_categories_index_df,
"Protein Accession")
# Joining 'aro_categories.tsv' is useless: the resulting 'ARO Category' is filled by NaN
# Join 'aro.tsv'
aro_df = pd.read_table(os.path.join(self.reference_dir, "ontology",
"aro.tsv"),
sep='\t',
header=0)
aro_df.rename(columns={
"Accession": "ARO Accession",
"Name": "ARO Name"
},
inplace=True)
self.nfasta_df = Utilities.left_merge(self.nfasta_df, aro_df,
"ARO Accession")
self.nfasta_df = Utilities.combine_duplicate_rows(
self.nfasta_df, "reference_id")
def annotate(self):
# Process nucleotide FASTA
self._raw_nfasta_df = pd.read_table(self.annotation_file, sep="\t", header=0)
raw_nfasta_headers = self._raw_nfasta_df["former_id"].values.tolist()
processed_nfasta_headers = [Utilities.dict2pd_series(i) for i in
Utilities.multi_core_queue(self._mp_parse_nfasta_header, raw_nfasta_headers)]
self._processed_nfasta_df = Utilities.merge_pd_series_list(processed_nfasta_headers).sort_values("former_id")
self.nfasta_df = Utilities.left_merge(self._raw_nfasta_df, self._processed_nfasta_df, "former_id")
# Process protein FASTA
raw_pfasta_headers = sorted(set([j for j in [re.sub("^>", "", i).strip() for i in
open(self._raw_pfasta_file, mode="r", encoding="utf-8") if
i.startswith(">")] if len(j) > 0]))
processed_pfasta_headers = [Utilities.dict2pd_series(i) for i in
Utilities.multi_core_queue(self._mp_parse_nfasta_header, raw_pfasta_headers)]
self.pfasta_df = Utilities.merge_pd_series_list(processed_pfasta_headers).sort_values("former_id")
self.pfasta_df.rename(columns={"geninfo_id": "protein_geninfo_id", "refseq_id": "genpept_id",
"description": "protein_description", "host": "protein_host"}, inplace=True)
self.merged_df = Utilities.left_merge(self.nfasta_df, self.pfasta_df, "tadb_id", "category", "gene_symbol")
self.merged_df = Utilities.combine_duplicate_rows(self.merged_df, "reference_id")
