Agent skill

Rnaseq De

by ClawBio in ClawBio/ClawBio

Differential expression analysis for bulk RNA-seq and pseudo-bulk count matrices with QC, PCA, and contrast testing.

MITAuto-check passedResearch & Science

Install Rnaseq De

skills CLI
$ npx skills add ClawBio/ClawBio --skill rnaseq-de -a claude-code

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

GitHub CLI
$ gh skill install ClawBio/ClawBio rnaseq-de --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/ClawBio/ClawBio.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/rnaseq-de .claude/skills/rnaseq-de && 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
rnaseq-de
GitHub stars
1.2k
Used in
1 other repo
Token cost
~565 tokens
SKILL.md length
112 words
Files
7
Skills in repo
104
Repo updated
First seen
Licence
MIT

At a glance

Differential expression analysis for bulk RNA-seq and pseudo-bulk count matrices with QC, PCA, and contrast testing.

  • Works in 6 steps: Input validation for count matrix and… → Pre-DE QC (library size, detected genes,… → PCA visualisation on normalized expression → …
  • Tasks that involve Bioinformatics
  • SKILL.md covers Core Capabilities, Input Contract, Output Structure and Usage, plus 1 more section
  • Runs Python scripts from its folder; calls python

What it does

Rnaseq De is an agent skill from ClawBio/ClawBio. Differential expression analysis for bulk RNA-seq and pseudo-bulk count matrices with QC, PCA, and contrast testing.

Its SKILL.md is about 570 tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files (for example `rnaseq_de.py` and `tests/test_rnaseq_de.py`).

It sits in Research & Science, covering Bioinformatics. The repository describes itself as: 🦖 ClawBio - The first bioinformatics-native AI agent skill library. Local-first. Reproducible. Open. Free. The licence is MIT.

When your agent uses it

  • Tasks that involve Bioinformatics

Example prompts

  • “/rnaseq-de”

Requirements

  • Python 3

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. Input validation for count matrix and sample metadata
  2. Pre-DE QC (library size, detected genes, low-count filtering)
  3. PCA visualisation on normalized expression
  4. Differential expression from formula + contrast
  5. Volcano and MA plots
  6. Markdown report with reproducibility files

What it can do on your machine

Read from SKILL.md and the folder at commit dece754. 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

Rnaseq De loads about 565 tokens when it runs. Until then it costs about 32 tokens; SKILL.md has 112 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~32
When it runs · the whole SKILL.md, loaded when a task matches
~565

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 ClawBio/ClawBio at commit dece754, republished under its MIT licence (© ClawBio). 112 words, ~565 tokens.

Download SKILL.mdSave it as .claude/skills/rnaseq-de/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.
name
rnaseq-de
description
Differential expression analysis for bulk RNA-seq and pseudo-bulk count matrices with QC, PCA, and contrast testing.
license
MIT
metadata.version
0.1.0
metadata.tags
rna-seq, differential expression, bulk, pseudo-bulk, transcriptomics, DESeq2, PyDESeq2, QC, PCA

🧬 RNA-seq Differential Expression

This skill performs differential expression on bulk RNA-seq or pseudo-bulk count matrices.

Core Capabilities

  1. Input validation for count matrix and sample metadata
  2. Pre-DE QC (library size, detected genes, low-count filtering)
  3. PCA visualisation on normalized expression
  4. Differential expression from formula + contrast
  5. Volcano and MA plots
  6. Markdown report with reproducibility files

Input Contract

  • Count matrix (.csv or .tsv): rows are genes, columns are samples, first column is gene identifier
  • Metadata table (.csv or .tsv): one row per sample, must include sample_id
  • Formula: e.g. ~ condition or ~ batch + condition
  • Contrast: factor,numerator,denominator (e.g. condition,treated,control)

Output Structure

rnaseq_de_report/
├── report.md
├── result.json
├── figures/
│   ├── pca.png
│   ├── volcano.png
│   └── ma_plot.png
├── tables/
│   ├── qc_summary.csv
│   ├── normalized_counts.csv
│   └── de_results.csv
└── reproducibility/
    ├── commands.sh
    ├── environment.yml
    └── checksums.sha256

Usage

bash
python rnaseq_de.py \
  --counts counts.csv \
  --metadata metadata.csv \
  --formula "~ batch + condition" \
  --contrast "condition,treated,control" \
  --output report_dir

Safety

  • Local-only processing
  • Warn before overwriting existing output
  • Report-level disclaimer required

© ClawBio, MIT. 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 6 other files in skills/rnaseq-de of ClawBio/ClawBio.

  • SKILL.md
  • examples/demo_counts.csv
  • examples/demo_metadata.csv
  • rnaseq_de.py
  • tests/fixtures/pseudobulk_counts.csv
  • tests/fixtures/pseudobulk_metadata.csv
  • tests/test_rnaseq_de.py

Open the folder on GitHubat commit dece754

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in ClawBio/ClawBio, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Rnaseq De next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Rnaseq De compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Rnaseq De this skillClawBio/ClawBio1.2k1 repos~565Automated safety check: PassMIT
Alphagenome Single Variant Analysisgoogle-deepmind/science-skills3.2k2 repos~3kAutomated safety check: NotesApache-2.0
13C Metabolic Flux AnalysisK-Dense-AI/scientific-agent-skills48k1 repos~3.2kAutomated safety check: PassMIT
Clinvar Databasegoogle-deepmind/science-skills3.2k2 repos~3.9kAutomated safety check: NotesApache-2.0
Metabolic Study Planneraiming-lab/AutoResearchClaw15k—~1.9kAutomated safety check: PassMIT
Dbsnp Databasegoogle-deepmind/science-skills3.2k2 repos~3.4kAutomated safety check: NotesApache-2.0

Similar skills

  • Alphagenome Single Variant Analysis

    google-deepmind/science-skills

    Analyzes genetic variant effects on gene expression (RNA-seq), chromatin accessibility (DNASE), histone marks (ChIP), and transcription factors using the AlphaGenome API.

    3.2k GitHub starsUsed in 2 repos~3k tokens
    Research & ScienceAuto-check: notes
  • 13C Metabolic Flux Analysis

    K-Dense-AI/scientific-agent-skills

    Estimates reaction fluxes inside cells from steady-state carbon-13 labeling data with a bundled mfapy-based solver, and reports which fluxes the data pin down.

    48k GitHub starsUsed in 1 repo~3.2k tokens
    Research & ScienceAuto-check passed
  • Clinvar Database

    google-deepmind/science-skills

    A skill your agent uses when needing clinical significance, pathogenicity classifications (e.g., Pathogenic, Benign, VUS), clinical evidence rationales, or finding "hard positive" benchmark controls…

    3.2k GitHub starsUsed in 2 repos~3.9k tokens
    Research & ScienceAuto-check: notes
  • Metabolic Study Planner

    aiming-lab/AutoResearchClaw

    Turns a broad metabolic modelling topic into a concrete, paper-shaped plan with organism, model, perturbations, metrics and figures before any FBA code is written.

    15k GitHub stars~1.9k tokensUpdated 1 mo ago
    Research & ScienceAuto-check passed
  • Dbsnp Database

    google-deepmind/science-skills

    A skill your agent uses when you want to look up, map, and search for short genetic variants (SNPs, indels) in NCBI's dbSNP database.

    3.2k GitHub starsUsed in 2 repos~3.4k tokens
    Research & ScienceAuto-check: notes
  • MFA Pipeline Orchestrator

    aiming-lab/AutoResearchClaw

    Runs a metabolic flux analysis from model loading to phenotype prediction and figures by handing work to four sub-agents in sequence.

    15k GitHub stars~923 tokensUpdated 1 mo ago
    Research & ScienceAuto-check passed

More from ClawBio/ClawBio

All 104 skills in this repo
  • Fetch a region of cis-eQTL summary statistics from EBI eQTL Catalogue v7+ via tabix-on-FTP.

    1.2k GitHub starsUsed in 1 repo~4.7k tokens
    Auto-check passed
  • Xena Tcga Gene Query

    ClawBio/ClawBio

    Query TCGA tumor biology through the ucscxenatoolspy API. An agent skill from ClawBio/ClawBio.

    1.2k GitHub stars~4.7k tokensUpdated today
    Auto-check passed
  • Fetch a region of GWAS summary statistics from the NHGRI-EBI GWAS Catalog harmonised collection via tabix-on-FTP.

    1.2k GitHub starsUsed in 1 repo~3.5k tokens
    Auto-check passed
  • Dnasp

    ClawBio/ClawBio

    Population genetics of pre-aligned DNA sequences or multi-sample VCFs using selected DnaSP 6 methods.

    1.2k GitHub stars~5.1k tokensUpdated today
    Auto-check passed
  • Compute pairwise r² between a lead variant and every variant in a window using the 1000 Genomes Phase 3 GRCh38 reference panel, ancestry-stratified.

    1.2k GitHub stars~3.9k tokensUpdated today
    Auto-check passed
  • Ncbi Datasets

    ClawBio/ClawBio

    Download genomes, genes, virus sequences, and taxonomy data from NCBI using the datasets and dataformat CLI tools.

    1.2k GitHub starsUsed in 1 repo~2.8k tokens
    Auto-check passed

Questions about Rnaseq De

What does Rnaseq De do?

Differential expression analysis for bulk RNA-seq and pseudo-bulk count matrices with QC, PCA, and contrast testing. Rnaseq De is an agent skill from ClawBio/ClawBio. Differential expression analysis for bulk RNA-seq and pseudo-bulk count matrices with QC, PCA, and contrast testing.

When should I use Rnaseq De?

Rnaseq De fits situations like: tasks that involve Bioinformatics.

How do I install Rnaseq De in Claude Code?

Run `npx skills add ClawBio/ClawBio --skill rnaseq-de -a claude-code`. Or copy the skill folder (skills/rnaseq-de in ClawBio/ClawBio) into .claude/skills/rnaseq-de in your project. Claude Code loads it when a task matches its description.

How do I install Rnaseq De in Codex?

Run `npx skills add ClawBio/ClawBio --skill rnaseq-de -a codex`. Or copy the skill folder (skills/rnaseq-de in ClawBio/ClawBio) into .agents/skills/rnaseq-de in your project. Codex loads it when a task matches its description.

Can I use Rnaseq De 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 ClawBio/ClawBio --skill rnaseq-de -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/rnaseq-de, .gemini/skills/rnaseq-de, .github/skills/rnaseq-de and .opencode/skills/rnaseq-de in your project.

What does Rnaseq De need to run?

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

Does Rnaseq De 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 Rnaseq De 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 Rnaseq De use?

Rnaseq De is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Rnaseq De use?

About 565 tokens (SKILL.md is roughly 2.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Rnaseq De?

Skills that share tags, products or a category with Rnaseq De: Alphagenome Single Variant Analysis (google-deepmind/science-skills, 3.2k stars), 13C Metabolic Flux Analysis (K-Dense-AI/scientific-agent-skills, 48k stars), Clinvar Database (google-deepmind/science-skills, 3.2k stars) and Metabolic Study Planner (aiming-lab/AutoResearchClaw, 15k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Rnaseq De?

ClawBio (a GitHub organization) maintains it in ClawBio/ClawBio, which has 1,154 GitHub stars. The repository holds 104 skills in this directory. The repository was last updated on October 8, 2026.

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