Source code for indra.sources.acsn.processor

from typing import Union

from indra.statements import *
from import bio_ontology
from indra.databases.hgnc_client import get_hgnc_id
from indra.ontology.standardize import get_standard_agent

rel_mapping = {
    'CATALYSIS': Activation,
    'INHIBITION': Inhibition,

[docs]class AcsnProcessor: """Processes Atlas of cancer signalling network (ACSN) relationships into INDRA statements Attributes ---------- relations_df : pandas.DataFrame A tab-separated data frame which consists of binary relationship between proteins with PMIDs. correspondence_dict : dict A dictionary with correspondences between ACSN entities and their HGNC symbols. """ def __init__(self, relations_df, correspondence_dict): """Constructor for AcsnProcessor class""" self.relations_df = relations_df self.correspondence_dict = correspondence_dict self.fplx_lookup = _make_famplex_lookup() self.statements = []
[docs] def extract_statements(self): """Return INDRA Statements Extracted from ACSN relations.""" for _, row in self.relations_df.iterrows(): acsn_agent_a, stmt_types, acsn_agent_b, pmids = list(row) stmt_type = get_stmt_type(stmt_types) if stmt_type: agent_a = self.get_agent(acsn_agent_a) agent_b = self.get_agent(acsn_agent_b) if agent_a and agent_b: if str(pmids) == 'nan': evs = [Evidence(source_api='acsn')] else: evs = [Evidence(source_api='acsn', pmid=pmid) for pmid in pmids.split(';')] if stmt_type == Complex: stmt = stmt_type([agent_a, agent_b], evidence=evs) else: stmt = stmt_type(agent_a, agent_b, evidence=evs) self.statements.append(stmt)
[docs] def get_agent(self, acsn_agent: str) -> Union[Agent, None]: """Return an INDRA Agent corresponding to an ACSN agent. Parameters ---------- acsn_agent : Agent extracted from the relations statement data frame Returns ------- : Returns INDRA agent with HGNC or FamPlex ID in db_refs. If there are no groundings available, we return None. """ mapping = self.correspondence_dict.get(acsn_agent) if not mapping: return None if len(mapping) == 1: hgnc_id = get_hgnc_id(mapping[0]) if hgnc_id: db_refs = {'HGNC': hgnc_id} return get_standard_agent(mapping[0], db_refs=db_refs) else: fplx_rel = self.fplx_lookup.get(tuple(sorted( self.correspondence_dict[acsn_agent]))) if fplx_rel: db_refs = {'FPLX': fplx_rel} return get_standard_agent(fplx_rel, db_refs=db_refs) return None
[docs]def get_stmt_type(stmt_type: str) -> Union[None, Statement]: """Return INDRA statement type from ACSN relation. Parameters ---------- stmt_type : An ACSN relationship type Returns ------- : INDRA equivalent of the ACSN relation type or None if a mappings is not available. """ if stmt_type in rel_mapping: mapped_stmt_type = rel_mapping[stmt_type] return mapped_stmt_type
def _make_famplex_lookup(): """Create a famplex lookup dictionary. Keys are sorted tuples of HGNC gene names and values are the corresponding FamPlex ID. """ fplx_lookup = {} bio_ontology.initialize() for node in bio_ontology.nodes: ns, id = bio_ontology.get_ns_id(node) if ns == 'FPLX': children = bio_ontology.get_children(ns, id) hgnc_children = [bio_ontology.get_name(*c) for c in children if c[0] == 'HGNC'] fplx_lookup[tuple(sorted(hgnc_children))] = id return fplx_lookup