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rnaseq-plot

analyze and visualize RNA-seq data

Published by MiniMax Updated Aug 27
Covers Data Visualization Data Analysis Bioinformatics RNA-seq

Description

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.md

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.

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