Claude Skill MartBrowse skillsQuick linesLearn by videoTerminal guideWhat is a Skill?
 
← Back to list

PyDESeq2 Differential Expression

An end-to-end guide for bulk RNA-seq differential expression with PyDESeq2 — formulaic designs, Wald tests, FDR correction, LFC shrinkage, and plots.

Data & AnalyticsAdvanced★ 33,030⑂ 3,248AI score 8/10Last updated: Aug 9, 2026

What it does

  • Runs the full DESeq2 pipeline in Python: size factors → dispersion estimation → GLM fit → Wald tests → Benjamini-Hochberg adjustment.
  • Covers formulaic design strings (~batch + condition), multi-factor designs, interaction terms, and explicit contrast specification.
  • Includes gene/sample filtering, significance filtering and ranking, volcano and MA plot code, plus CSV and portable H5AD export.
  • Ships a CLI script scripts/run_deseq2_analysis.py for batch runs and a troubleshooting section for index mismatches, transposed matrices, and non-full-rank design matrices.

Who it's for

  • Bioinformaticians and grad students analyzing bulk RNA-seq counts.
  • Teams porting R DESeq2 workflows into Python pipelines.
  • Anyone needing to control batch effects or covariates in multi-factor designs.

Examples

  1. "Run treated vs control DE analysis on counts.csv and metadata.csv" → generates code from filtering through the significant-gene count.
  2. "Adjust for batch effects" → CLI invocation with --design "~batch + condition" and the rule that adjustment variables come first.
  3. "No significant genes found" → diagnostic snippets for dispersion distribution, size factors, and p-value histograms.

· · · Install guide · · ·

Try it now, no install

Paste this into Claude to use the skill without installing anything.

Read the instructions in this file and follow them to help me:
https://raw.githubusercontent.com/K-Dense-AI/scientific-agent-skills/HEAD/skills/pydeseq2/SKILL.md

What I want: (describe your task here)

If Claude can't open the link, open it yourself and paste the contents instead.

↓ If it works for you, download the ZIP below and install it. Then it runs on its own — no pasting each time.

Install in the Claude app (no terminal)
  1. Download the ZIP with the button below.
  2. In Claude, open Settings → Capabilities and turn on 'Code execution and file creation'. (one time)
  3. Go to Customize → Skills → + → 'Upload a skill' and upload the ZIP.
↓ Download ZIP
Install in Claude Code

Let Claude do it — paste this into Claude Code

Install the skill I found on Claude Skill Mart.
Copy the skills/pydeseq2 folder from the GitHub repo K-Dense-AI/scientific-agent-skills into my ~/.claude/skills/pydeseq2/.
When it's done, tell me in one line what this skill can do.

Install with a command instead

git clone https://github.com/K-Dense-AI/scientific-agent-skills.git && mkdir -p ~/.claude/skills && cp -r scientific-agent-skills/skills/pydeseq2 ~/.claude/skills/

⚠ This is a third-party skill. Check the source repository before installing.

  1. Confirm Python 3.11 or newer: python --version
  2. Install dependencies: uv pip install pydeseq2==0.5.4 (add matplotlib seaborn for plots).
  3. Clone the skill repository: git clone https://github.com/K-Dense-AI/scientific-agent-skills.git
  4. Copy the skill into Claude Code: mkdir -p ~/.claude/skills && cp -r scientific-agent-skills/skills/pydeseq2 ~/.claude/skills/
  5. Verify that ~/.claude/skills/pydeseq2/ contains both references/ and scripts/.
  6. Restart Claude Code and try a prompt like "Run a PyDESeq2 differential expression analysis on my counts matrix."
View source on GitHub ↗License: MIT