pydeseq2
This skill provides a Python implementation of DESeq2 for differential gene expression analysis from RNA-seq count data. It covers data loading, statistical testing with Wald tests, multiple testing correction, and result visualization. The documentation includes clear workflows, troubleshooting guides, and best practices for experimental design.
Packaged view
This page reorganizes the original catalog entry around fit, installability, and workflow context first. The original raw source lives below.
Install command
npx @skill-hub/cli install microck-ordinary-claude-skills-pydeseq2
Repository
Skill path: skills_all/claude-scientific-skills/scientific-skills/pydeseq2
This skill provides a Python implementation of DESeq2 for differential gene expression analysis from RNA-seq count data. It covers data loading, statistical testing with Wald tests, multiple testing correction, and result visualization. The documentation includes clear workflows, troubleshooting guides, and best practices for experimental design.
Open repositoryBest for
Primary workflow: Design Product.
Technical facets: Data / AI, Designer, Testing.
Target audience: AI/ML teams looking for install-ready agent workflows..
License: Unknown.
Original source
Catalog source: SkillHub Club.
Repository owner: Microck.
This is still a mirrored public skill entry. Review the repository before installing into production workflows.
What it helps with
- Install pydeseq2 into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
- Review https://github.com/Microck/ordinary-claude-skills before adding pydeseq2 to shared team environments
- Use pydeseq2 for ai/ml workflows
Works across
Favorites: 0.
Sub-skills: 0.
Aggregator: No.