metabolomics-pathway-enrichment

metabolomics-pathway-enrichment

When to use

Run metabolite-name ORA against explicit pathways or nine demo pathways. External mummichog/FELLA are required for their own methods.

Use from a step

import pandas as pd
import json
from pathlib import Path
from skills._sdk.notebook import load_skill, read_input, write_output
library = load_skill("metabolomics-pathway-enrichment")
data = read_input('features.csv', reader=pd.read_csv)
pathways = read_input('pathways.json', reader=lambda path: json.loads(Path(path).read_text()))
result = library.enrich(data['metabolite'], pathways=pathways)
write_output(result, 'tables/result.csv')

examples/example_step.py runs a seeded synthetic example through the step runner and writes a table and Figure. Computations return new DataFrames, leave the input unchanged and expose diagnostics through run_info(result). Plotting functions write no files.

API

enrich(data, *, method='ora', pathways=None)

Test case-insensitive exact metabolite-name overlap by hypergeometric ORA.

:param data: Iterable of metabolite names; duplicates count once in each overlap. :param method: CLI default ora, the only implemented method. :param pathways: Required mapping of pathway names to metabolites lists and kegg_id labels; use demo_pathways() only for demonstrations. :returns: A new table; BH FDR covers pathways with at least one hit, matching the CLI. :raises ValueError: A requested method is unimplemented or reference is empty.

demo_pathways()

Return an independent copy of the nine illustrative pathway sets.

:returns: A mapping for explicit demo use, not a complete pathway database.

run_info(data, *, keep=True)

Read diagnostics attached to a returned table.

:param data: DataFrame returned by this library. :param keep: Default True; use False in the CLI to remove diagnostics. :returns: An independent dictionary describing the run. :raises ValueError: The table carries no run_info.