xCRG

Reusable xCRG package for MVP2 gene activity/abundance inferred TRAPI queries.

This package contains the xCRG core logic only. Callers such as ARAX or Shepherd provide runtime configuration for Retriever, NGD, timeouts, and data tiers.

Current Scope

• Detect MVP2 xCRG query shape.
• Build direct and TF-mediated Retriever queries.
• Filter, merge, rank, and format xCRG results.
• Return a TRAPI response with support graphs and NGD analysis support.
• Preserve Retriever-provided KG node metadata verbatim in final evidence graphs.
• Limit final answer pairs to the configured top result count.
• Keep Shepherd/ARAX service plumbing outside the package.

Usage

from xcrg import XCRGConfig, run_xcrg

config = XCRGConfig(
    retriever_url="https://example-retriever/query",
    ngd_db_path="/path/to/curie_ngd.sqlite",
    tf_path=None,  # uses bundled transcription factor list
    timeout=210,
    tiers=[0],
    max_results=500,
)

response = run_xcrg(query, config=config)

Async callers can use:

from xcrg import async_run_xcrg

response = await async_run_xcrg(query, config=config)

Local Tests

PYTHONPATH=src python -m pytest tests

Notes

• Do not commit NGD SQLite databases.
• Do not add Shepherd-specific imports such as shepherd_utils.
• Retriever URL and NGD path are caller-provided config so deployment changes do not require republishing the package.
• xCRG does not infer or repair Retriever node categories/names; Retriever node objects used as evidence are passed through as returned.
• If a user-pinned query endpoint is referenced by evidence but Retriever omits its KG node, xCRG uses only the explicit category metadata supplied in the query graph for that endpoint.