# Bioconductor Microbiome

Utilities for microbiome analysis.

- Repository: https://github.com/bioMate-AI/biomate-bioconductor-kb (793 stars)
- Category: Engineering
- License: see repository
- Last updated: 2026-06-20
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add bioMate-AI/biomate-bioconductor-kb --skill bioconductor-microbiome -g -a claude-code -y`
Codex: `npx skills add bioMate-AI/biomate-bioconductor-kb --skill bioconductor-microbiome -g -a codex -y`
Cursor: `npx skills add bioMate-AI/biomate-bioconductor-kb --skill bioconductor-microbiome -g -a cursor -y`
Gemini CLI: `npx skills add bioMate-AI/biomate-bioconductor-kb --skill bioconductor-microbiome -g -a gemini-cli -y`

## Description

Utilities for microbiome analysis.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# microbiome

## Dependencies & Environment

> Package-intrinsic requirements from the Bioconductor landing page, reproduce in any R environment.

- **Version:** 1.34.0 · **Bioconductor:** 3.23 · **R:** ≥ 4.6
- **Depends:** phyloseq, ggplot2
- **Imports:** Biostrings, compositions, dplyr, reshape2, Rtsne, scales, tibble, tidyr, vegan
- **Install:** `BiocManager::install("microbiome")`

## When to Use
- Facilitating `phyloseq`-based exploration and analysis of taxonomic profiling data.
- Performing manipulation, statistical analysis, and visualization of taxonomic profiling data.
- Standardizing analyses and developing best practices for targeted microbiome analysis.

## When NOT to Use
- For new projects or multi-omics data analysis, use the `miaverse` project instead, as `microbiome` development has been discontinued.
- For workflows based on the new `TreeSummarizedExperiment` data container, use `miaverse` packages instead of `microbiome`.

## Data Requirements
- Taxonomic profiling data in the independent `phyloseq` data format.

## Key Parameters
- No parameters are explicitly detailed in the provided vignette text.

## Best Practices
- Transition to the `miaverse` project and `TreeSummarizedExperiment` data container for added capabilities in multi-omics data analysis.
- Use the package to facilitate scalable exploration of population cohorts and targeted case-control studies.
- Rely on the independent `phyloseq` package and data structures for R-based microbiome analysis.

The rest: https://github.com/bioMate-AI/biomate-bioconductor-kb/blob/HEAD/skills/metagenomics/microbiome/SKILL.md