Registration Open for Bioc2024 July 24-26


microbiome biomarker analysis toolkit

Bioconductor version: Release (3.19)

To date, a number of methods have been developed for microbiome marker discovery based on metagenomic profiles, e.g. LEfSe. However, all of these methods have its own advantages and disadvantages, and none of them is considered standard or universal. Moreover, different programs or softwares may be development using different programming languages, even in different operating systems. Here, we have developed an all-in-one R package microbiomeMarker that integrates commonly used differential analysis methods as well as three machine learning-based approaches, including Logistic regression, Random forest, and Support vector machine, to facilitate the identification of microbiome markers.

Author: Yang Cao [aut, cre]

Maintainer: Yang Cao < at>

Citation (from within R, enter citation("microbiomeMarker")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

Tools for microbiome marker identification HTML R Script
Reference Manual PDF


biocViews DifferentialExpression, Metagenomics, Microbiome, Software
Version 1.10.0
In Bioconductor since BioC 3.14 (R-4.1) (2.5 years)
License GPL-3
Depends R (>= 4.1.0)
Imports dplyr, phyloseq, magrittr, purrr, MASS, utils, ggplot2, tibble, rlang, stats, coin, ggtree, tidytree, methods, IRanges, tidyr, patchwork, ggsignif, metagenomeSeq, DESeq2, edgeR, BiocGenerics, Biostrings, yaml, biomformat, S4Vectors, Biobase, ComplexHeatmap, ANCOMBC, caret, limma, ALDEx2, multtest, plotROC, vegan, pROC, BiocParallel
System Requirements
Bug Reports
See More
Suggests testthat, covr, glmnet, Matrix, kernlab, e1071, ranger, knitr, rmarkdown, BiocStyle, withr
Linking To
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package microbiomeMarker_1.10.0.tar.gz
Windows Binary
macOS Binary (x86_64) microbiomeMarker_1.10.0.tgz
macOS Binary (arm64) microbiomeMarker_1.10.0.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
Bioc Package Browser
Package Short Url
Package Downloads Report Download Stats