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DirichletMultinomial

Dirichlet-Multinomial Mixture Model Machine Learning for Microbiome Data

Bioconductor version: 3.23 · Package version: 1.54.0

Dirichlet-multinomial mixture models can be used to describe variability in microbial metagenomic data. This package is an interface to code originally made available by Holmes, Harris, and Quince, 2012, PLoS ONE 7(2): 1-15, as discussed further in the man page for this package, ?DirichletMultinomial.

Installation

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

BiocManager::install("DirichletMultinomial")

Details

MaintainerMartin Morgan <mtmorgan.xyz@gmail.com>
AuthorMartin Morgan [aut, cre] (ORCID: <https://orcid.org/0000-0002-5874-8148>)
LicenseLGPL-3
URLhttps://mtmorgan.github.io/DirichletMultinomial/
Bug Reportshttps://github.com/mtmorgan/DirichletMultinomial/issues
System Requirementsgsl
Downloads rank5789
Source branchRELEASE_3_23
biocViewsClassification, Clustering, ImmunoOncology, Metagenomics, Microbiome, Sequencing, Software

Documentation

Download

Follow the installation instructions to use this package in your R session.

Source packageDirichletMultinomial_1.54.0.tar.gz
Windows binary (x86_64)DirichletMultinomial_1.54.0.zip
macOS binary (arm64)DirichletMultinomial_1.54.0.tgz
macOS binary (x86_64)DirichletMultinomial_1.54.0.tgz
Dependencies

Depends: S4Vectors, IRanges

Imports: stats4, methods, BiocGenerics

Suggests: lattice, parallel, MASS, RColorBrewer, DT, knitr, rmarkdown, BiocStyle

Reverse dependencies

Imports Me (3): mia, miaViz, TFBSTools

Suggests Me (2): bluster, MicrobiotaProcess