Bioconductor release scheduled for October 29

maaslin3

This is the development version of maaslin3; for the stable release version, see maaslin3.

"Refining and extending generalized multivariate linear models for meta-omic association discovery"


Bioconductor version: Development (3.22)

MaAsLin 3 refines and extends generalized multivariate linear models for meta-omicron association discovery. It finds abundance and prevalence associations between microbiome meta-omics features and complex metadata in population-scale epidemiological studies. The software includes multiple analysis methods (including support for multiple covariates, repeated measures, and ordered predictors), filtering, normalization, and transform options to customize analysis for your specific study.

Author: William Nickols [aut, cre] ORCID iD ORCID: 0000-0001-8214-9746 , Jacob Nearing [aut]

Maintainer: William Nickols <willnickols at g.harvard.edu>

Citation (from within R, enter citation("maaslin3")):

Installation

To install this package, start R (version "4.5") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("maaslin3")

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

Documentation

Reference Manual PDF

Details

biocViews Metagenomics, Microbiome, MultipleComparison, Normalization, Software
Version 1.1.0
In Bioconductor since BioC 3.21 (R-4.5) (< 6 months)
License MIT + file LICENSE
Depends R (>= 4.4)
Imports dplyr, plyr, pbapply, lmerTest, parallel, lme4, optparse, logging, multcomp, ggplot2, RColorBrewer, patchwork, scales, rlang, tibble, ggnewscale, survival, methods, BiocGenerics, SummarizedExperiment, TreeSummarizedExperiment
System Requirements
URL http://huttenhower.sph.harvard.edu/maaslin3
Bug Reports https://github.com/biobakery/maaslin3/issues
See More
Suggests knitr, testthat (>= 2.1.0), rmarkdown, markdown, kableExtra
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Package Archives

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

Source Package
Windows Binary (x86_64) maaslin3_1.1.0.zip
macOS Binary (x86_64)
macOS Binary (arm64)
Source Repository git clone https://git.bioconductor.org/packages/maaslin3
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/maaslin3
Bioc Package Browser https://code.bioconductor.org/browse/maaslin3/
Package Short Url https://bioconductor.org/packages/maaslin3/
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