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Agent skill

Metabolomics Pathway Enrichment

by TianGzlab in TianGzlab/OmicsClaw

Load when running metabolite-name ORA against an explicit local pathway reference with BH-FDR; bundled pathway sets are for explicit demonstrations only.

Apache-2.0Auto-check passedData & Analytics

Install Metabolomics Pathway Enrichment

skills CLI
$ npx skills add TianGzlab/OmicsClaw --skill metabolomics-pathway-enrichment -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install TianGzlab/OmicsClaw metabolomics-pathway-enrichment --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/TianGzlab/OmicsClaw.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/metabolomics/metabolomics-pathway-enrichment .claude/skills/metabolomics-pathway-enrichment && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
metabolomics-pathway-enrichment
GitHub stars
161
Token cost
~1.1k tokens
SKILL.md length
382 words
Files
8 (incl. references)
Skills in repo
88
Repo updated
First seen
Licence
Apache-2.0

At a glance

Load when running metabolite-name ORA against an explicit local pathway reference with BH-FDR; bundled pathway sets are for explicit demonstrations only.

  • Data & Analytics work in your project
  • SKILL.md covers When to use, Use from a step, API and Methods and parameters, plus 5 more sections
  • Runs Python scripts from its folder; calls python

What it does

Metabolomics Pathway Enrichment is an agent skill from TianGzlab/OmicsClaw. Load when running metabolite-name ORA against an explicit local pathway reference with BH-FDR; bundled pathway sets are for explicit demonstrations only. Skip m/z annotation (use metabolomics-annotation) and topology analysis or online pathway retrieval (use external mummichog / FELLA or database tools).

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including reference files (for example `_api.py`, `examples/example_step.py` and `met_pathway.py`).

It sits in Data & Analytics. The repository describes itself as: Conversational & memory-enabled AI research partner for multi-omics analysis. CLI + Desktop App (installers in Releases). From biological idea to full research paper. The licence is Apache-2.0.

When your agent uses it

  • Data & Analytics work in your project

Example prompts

  • “/metabolomics-pathway-enrichment”

Requirements

  • Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit 90a3bec. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships script files (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Metabolomics Pathway Enrichment loads about 1.1k tokens when it runs, and up to ~1.6k if it reads all its reference files. Until then it costs about 84 tokens; SKILL.md has 382 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~84
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~1.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from TianGzlab/OmicsClaw at commit 90a3bec, republished under its Apache-2.0 licence (© TianGzlab). 382 words, ~1,116 tokens.

Download SKILL.mdSave it as .claude/skills/metabolomics-pathway-enrichment/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.
name
metabolomics-pathway-enrichment
description
Load when running metabolite-name ORA against an explicit local pathway reference with BH-FDR; bundled pathway sets are for explicit demonstrations only. Skip m/z annotation (use metabolomics-annotation) and topology analysis or online pathway retrieval (use external mummichog / FELLA or database tools).
trigger
metabolomics pathway, KEGG, MetaboAnalyst, enrichment, mummichog
tags
metabolomics, pathway, enrichment, ora, fisher, demo

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

python
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

<!-- api:begin generated from _api.py; regenerate with run.py api <skill dir> --write -->
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.

enrichment_figure(data, *, n_top=10)

Plot the strongest pathway overlaps by adjusted p value.

:param data: Results returned by enrich. :param n_top: Default 10; maximum number of pathways shown. :returns: A matplotlib Figure. :raises KeyError: pathway or fdr is absent.

<!-- api:end -->
Show full SKILL.md (142 more words)Show less

Methods and parameters

Matching is case-insensitive exact name equality, not substring matching. The background is the union of reference members. Hypergeometric survival probabilities and BH correction apply to pathways with at least one hit, matching the legacy CLI.

Gotchas

  • enrich requires explicit pathways= and implements only ora. Missing reference data and fella/mummichog requests fail. demo_pathways() explicitly selects the nine illustrative sets; never use these as biological evidence.
  • tables/pathway_enrichment.csv has a stable schema even with no overlap. result.json records the reference scope in data.run_info.reference_scope.

Inputs and outputs

CSV input; tables/pathway_enrichment.csv, report.md and result.json. Demo mode also writes its synthetic input CSV at the output root. Real input also requires a JSON reference: {"pathway name": {"kegg_id": "identifier", "metabolites": ["glucose", "pyruvate"]}}. The function library returns objects; the CLI and step own file writes.

CLI

bash
python skills/metabolomics/metabolomics-pathway-enrichment/met_pathway.py --demo --output /tmp/metabolomics_pathway_enrichment
python skills/metabolomics/metabolomics-pathway-enrichment/met_pathway.py --input features.csv --pathway-file pathways.json --output /tmp/metabolomics_pathway_real

See also

Dependencies

numpy, pandas, scipy, matplotlib

© TianGzlab, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 7 other files (references) in skills/metabolomics/metabolomics-pathway-enrichment of TianGzlab/OmicsClaw.

  • SKILL.md
  • _api.py
  • examples/example_step.py
  • met_pathway.py
  • references/methodology.md
  • references/output_contract.md
  • references/parameters.md
  • tests/test_api.py

Open the folder on GitHubat commit 90a3bec

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TimesFM Forecastinggoogle-research/timesfm34k—~4.7kAutomated safety check: PassApache-2.0

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Categories

Questions about Metabolomics Pathway Enrichment

What does Metabolomics Pathway Enrichment do?

Load when running metabolite-name ORA against an explicit local pathway reference with BH-FDR; bundled pathway sets are for explicit demonstrations only. Metabolomics Pathway Enrichment is an agent skill from TianGzlab/OmicsClaw. Load when running metabolite-name ORA against an explicit local pathway reference with BH-FDR; bundled pathway sets are for explicit demonstrations only.

When should I use Metabolomics Pathway Enrichment?

Metabolomics Pathway Enrichment fits situations like: data & Analytics work in your project.

How do I install Metabolomics Pathway Enrichment in Claude Code?

Run `npx skills add TianGzlab/OmicsClaw --skill metabolomics-pathway-enrichment -a claude-code`. Or copy the skill folder (skills/metabolomics/metabolomics-pathway-enrichment in TianGzlab/OmicsClaw) into .claude/skills/metabolomics-pathway-enrichment in your project. Claude Code loads it when a task matches its description.

How do I install Metabolomics Pathway Enrichment in Codex?

Run `npx skills add TianGzlab/OmicsClaw --skill metabolomics-pathway-enrichment -a codex`. Or copy the skill folder (skills/metabolomics/metabolomics-pathway-enrichment in TianGzlab/OmicsClaw) into .agents/skills/metabolomics-pathway-enrichment in your project. Codex loads it when a task matches its description.

Can I use Metabolomics Pathway Enrichment in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add TianGzlab/OmicsClaw --skill metabolomics-pathway-enrichment -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/metabolomics-pathway-enrichment, .gemini/skills/metabolomics-pathway-enrichment, .github/skills/metabolomics-pathway-enrichment and .opencode/skills/metabolomics-pathway-enrichment in your project.

What does Metabolomics Pathway Enrichment need to run?

Going by SKILL.md and its folder, Metabolomics Pathway Enrichment needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Metabolomics Pathway Enrichment access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Metabolomics Pathway Enrichment safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Metabolomics Pathway Enrichment use?

Metabolomics Pathway Enrichment is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Metabolomics Pathway Enrichment use?

About 1.1k tokens (SKILL.md is roughly 4.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 450 tokens, read only when the agent opens those files.

What are the alternatives to Metabolomics Pathway Enrichment?

Skills that share tags, products or a category with Metabolomics Pathway Enrichment: Matplotlib (zLanqing/codex-claude-academic-skills, 4.7k stars), Exploratory Data Analysis (spacering-net/codeg, 3.9k stars), Scikit Learn (zLanqing/codex-claude-academic-skills, 4.7k stars) and Chart Visualization (bytedance/deer-flow, 84k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Metabolomics Pathway Enrichment?

TianGzlab (a GitHub organization) maintains it in TianGzlab/OmicsClaw, which has 161 GitHub stars. The repository holds 88 skills in this directory. The repository was last updated on October 7, 2026.

Source: TianGzlab/OmicsClaw on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.