# Rnaseq Plot

> Use when the user already has an RNA-seq count or expression matrix and needs downstream plots or analysis (normalize, PCA, DESeq2/edgeR/limma, volcano, heatmap, GO/KEGG, GSEA, WGCNA). Call the rnaseq-plot MCP tools named rgraph_*; do not redraw in Python.

- Skill: `minimax-ai/rnaseq-plot` (Agent Skill)
- Install (CLI): `npx skillmds@latest add minimax-ai/rnaseq-plot`
- Raw SKILL.md: https://api.skillmd.com/api/skills/minimax-ai/rnaseq-plot/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: MiniMax AI (https://skillmd.com/u/minimax-ai)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/minimax-ai/rnaseq-plot

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# rnaseq-plot

Use the `rnaseq-plot` MCP server. Tool functions are still named `rgraph_*`. Prefer R-rendered png+pdf over matplotlib copies.

## Typical order

1. `rgraph_env` — confirm Rscript and packages
2. `rgraph_normalize` / `rgraph_pca` / `rgraph_correlation` as needed
3. `rgraph_diff` — default significance metric is **padj**, not raw p-value
4. `rgraph_volcano`, `rgraph_heatmap`, `rgraph_enrich`, `rgraph_gsea`, `rgraph_wgcna` as requested

Required table columns are in the Plugin README (`sample_name`/`group`, `gene_id`, counts).

If Rscript is missing, return the generated `.R` script and the command to run it. If a package is missing, return the install hint from the tool. Do not pretend the figure was drawn.