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"Multivariable Association Discovery in Population-scale Meta-omics Studies"

Bioconductor version: Release (3.19)

MaAsLin2 is comprehensive R package for efficiently determining multivariable association between clinical metadata and microbial meta'omic features. MaAsLin2 relies on general linear models to accommodate most modern epidemiological study designs, including cross-sectional and longitudinal, and offers a variety of data exploration, normalization, and transformation methods. MaAsLin2 is the next generation of MaAsLin.

Author: Himel Mallick [aut], Ali Rahnavard [aut], Lauren McIver [aut, cre]

Maintainer: Lauren McIver <lauren.j.mciver at>

Citation (from within R, enter citation("Maaslin2")):


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:

Maaslin2 HTML R Script
Reference Manual PDF


biocViews Metagenomics, Microbiome, Normalization, Software
Version 1.18.0
In Bioconductor since BioC 3.10 (R-3.6) (4.5 years)
License MIT + file LICENSE
Depends R (>= 3.6)
Imports robustbase, biglm, pcaPP, edgeR, metagenomeSeq, pbapply, car, dplyr, vegan, chemometrics, ggplot2, pheatmap, logging, data.table, lmerTest, hash, optparse, grDevices, stats, utils, glmmTMB, MASS, cplm, pscl, lme4, tibble
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Suggests knitr, testthat (>= 2.1.0), rmarkdown, markdown
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Imports Me benchdamic, Macarron, MMUPHin, ggpicrust2
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Follow Installation instructions to use this package in your R session.

Source Package Maaslin2_1.18.0.tar.gz
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macOS Binary (x86_64) Maaslin2_1.18.0.tgz
macOS Binary (arm64) Maaslin2_1.18.0.tgz
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Source Repository (Developer Access) git clone
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