What is sc-enrichment?

A pathway analysis for ranked gene lists from single-cell RNA sequencing, using collections of genes that represent biological processes. It checks whether selected pathways are unusually represented or concentrated near the top of a ranking.

Use it for over-representation analysis, GSEA, or GSVA on groups of marker or differentially expressed genes.

It turns long marker or differential-expression gene lists into more interpretable biological themes.

sc-enrichment — Skill for Claude Code and Codex by TianGzlab

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add TianGzlab/OmicsClaw --skill sc-enrichment

Clone the repo

git clone --depth 1 https://github.com/TianGzlab/OmicsClaw

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/tiangzlab/omicsclaw/sc-enrichment/github.svg)](https://agentmods.dev/skills/tiangzlab/omicsclaw/sc-enrichment)

Your own site

<a href="https://agentmods.dev/skills/tiangzlab/omicsclaw/sc-enrichment"><img src="https://agentmods.dev/badge/skills/tiangzlab/omicsclaw/sc-enrichment/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/tiangzlab/omicsclaw/sc-enrichment"><img src="https://agentmods.dev/badge/skills/tiangzlab/omicsclaw/sc-enrichment.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 71 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 2,131 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector warn 7 Sept 2026

SkillSpector: 1 finding, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

high Rogue Agent · line 3
Skill modifies its own code, configuration, or behavior at runtime. Self-modification enables an agent to escalate privileges, disable safety constraints, or install persistent backdoors.

Fix: Prevent the skill from modifying its own code, SKILL.md, or configuration files. Treat skill files as read-only at runtime.

How audits are shown

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00071	$0.02131
Opus 5	$0.00036	$0.01066
Sonnet 5	$0.00014	$0.00426
Haiku 4.5	$0.00007	$0.00213

Measured 6d ago against content hash 6e45c911674e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

sc-enrichment scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.

The scan reads SKILL.md. This mod also ships 3 executable files (sc_enrichment.py, tests/test_sc_enrichment_methods.py, tests/test_sc_enrichment.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/singlecell/scrna/sc-enrichment/SKILL.md · 158 lines

How it starts

The opening of the file, as written. The whole thing — 158 lines — stays where its author put it; the contents beside it link to each section on GitHub.

sc-enrichment

When to use

The user has a clustered / labelled scRNA AnnData and wants per-group pathway enrichment from a marker / DE ranking against a gene-set library. Four methods × two engines:

ora (default) — over-representation analysis on the top-K markers per group (--ora-padj-cutoff / --ora-log2fc-cutoff / --ora-max-genes).
gsea — pre-ranked GSEA using the ranking metric from sc.tl.rank_genes_groups (--gsea-ranking-metric, --gsea-min-size / --gsea-max-size, etc.).
gsea_r — R-backed fgsea/clusterProfiler-style GSEA.
gsva_r — GSVA per-cell or per-group score matrix (R only; --groupby required).

Engine selection (--engine auto/python/r) is independent — auto picks the right engine for the method.

For per-cell scoring (no rankings, just gene sets) use sc-pathway-scoring. For de-novo factorisation (no gene sets) use sc-gene-programs.

Inputs & Outputs

Inputs

Input kinds: file, directory
Modalities: scrna
File types: .h5ad
Requires a preprocessed AnnData (X normalised, PCA/neighbours present)

Outputs

tables/cell_metadata.csv
tables/clusterprofiler_results.csv
tables/de_for_gsea_r.csv
tables/de_full.csv
tables/enrichment_results.csv
tables/enrichment_significant.csv
tables/group_expr_for_gsva.csv
tables/group_summary.csv
tables/gsea_input.csv
tables/gsea_r_results.csv
tables/gsea_running_scores.csv
tables/gsva_r_scores.csv
tables/markers_all.csv
tables/ora_input.csv
tables/ranking_input.csv
tables/top_terms.csv
figures/gsva_r_heatmap.png
figures/r_enrichment_bar.png
figures/r_enrichment_dotplot.png
figures/r_enrichment_enrichmap.png
figures/r_enrichment_lollipop.png
figures/r_enrichment_network.png
figures/r_gsea_mountain.png
figures/r_gsea_nes_heatmap.png
analysis_summary.txt
background_genes.txt
processed.h5ad
r_plot_metadata.json
report.md
result.json
Processed AnnData (saves_h5ad)

Read the full file on GitHub · 158 lines

Files

What ships with it

9 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

6d ago First seen · 158 lines · 71 tokens per session scan A 6e45c911674e

Subscribe to this mod's changes

sc-enrichment is a skill published in the GitHub repository TianGzlab/OmicsClaw (160 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 71 tokens to every session and 2,131 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

GSEA ORA Scientific bioinformatics decoupler enrichment gsva knowledge-graph llm-agent multi-agents pathway-enrichment scrna singlecell

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sc-enrichment

Getting it into your agent

Wrote this? Show the measurements

What it costs to keep this loaded

Grade A, and why

Nothing flagged

How it starts

sc-enrichment

When to use

Inputs & Outputs

What ships with it

What this file has done since we first saw it

Other skills, from other repositories

enrichment

spatial-enrichment

Virtual Embryo — atlas data + knowledge graph

pkpd-modeling

neuropixels-analysis

onekgpd