microbe

Downstream 16S / ITS microbiome analysis for MiniMax Code. vegan, DESeq2, edgeR, igraph, Hmisc, randomForest, and ggtree scripts are wrapped as MCP tools and rendered by local Rscript.

Figure types follow two public papers for layout (the Plugin does not include their data):

• Liu et al. 2023, Nature Microbiology
• Zhou et al. 2022, Nature Communications

Does not run DADA2/QIIME2. Start from a feature table.

Try it

I have feature_table.csv, taxonomy.csv, and metadata.csv (groups DP vs DSP). Draw alpha and beta
diversity, a genus stacked bar, DESeq2 differential abundance, and a co-occurrence network.

Expected result: the agent calls microbe_env, then microbe_alpha, microbe_beta, microbe_composition, microbe_diff, and microbe_network. png+pdf paths and key statistics are returned. Synthetic tables can be generated with python tests/prep_test.py for a dry run.

Requirements

• Python 3.10+ and uv on PATH.
• R with Rscript on PATH, or set MICROBE_RSCRIPT.
• R packages such as vegan, ggplot2, igraph; DESeq2/edgeR optional (tools degrade with install hints).
• Windows, macOS, and Linux.

Data and network

• Analyses are local on user CSVs. No telemetry.
• No credentials in the package.
• tests/prep_test.py writes synthetic OTU-like tables only.

License

MIT. See LICENSE.