Package: DirichletMultinomial 1.55.0

Martin Morgan

DirichletMultinomial: Dirichlet-Multinomial Mixture Model Machine Learning for Microbiome Data

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 This package is an interface to code originally made available by Holmes, Harris, and Quince, 2012, PLoS ONE 7(2): 1-15, as discussed further in the man page for this package, ?DirichletMultinomial.

Authors:Martin Morgan [aut, cre]

DirichletMultinomial_1.55.0.tar.gz
DirichletMultinomial_1.55.0.zip(r-4.7)DirichletMultinomial_1.55.0.zip(r-4.6)DirichletMultinomial_1.55.0.zip(r-4.5)
DirichletMultinomial_1.55.0.tgz(r-4.6-x86_64)DirichletMultinomial_1.55.0.tgz(r-4.6-arm64)DirichletMultinomial_1.55.0.tgz(r-4.5-x86_64)DirichletMultinomial_1.55.0.tgz(r-4.5-arm64)
DirichletMultinomial_1.55.0.tar.gz(r-4.7-arm64)DirichletMultinomial_1.55.0.tar.gz(r-4.7-x86_64)DirichletMultinomial_1.55.0.tar.gz(r-4.6-arm64)DirichletMultinomial_1.55.0.tar.gz(r-4.6-x86_64)
DirichletMultinomial_1.55.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
DirichletMultinomial/json (API)

# Install 'DirichletMultinomial' in R:
install.packages('DirichletMultinomial', repos = c('https://tempbioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/mtmorgan/dirichletmultinomial/issues

Pkgdown/docs site:https://mtmorgan.github.io

Uses libs:
  • gsl– GNU Scientific Library (GSL)
Datasets:
  • bestgrp - Data objects used for examples and the vignette
  • fit - Data objects used for examples and the vignette
  • xval - Data objects used for examples and the vignette

On BioConductor:DirichletMultinomial-1.55.0(bioc 3.24)DirichletMultinomial-1.54.0(bioc 3.23)

immunooncologymicrobiomesequencingclusteringclassificationmetagenomicsgsl

10.04 score 12 stars 27 packages 174 scripts 9.2k downloads 16 exports 4 dependencies

Last updated from:15e0e5b4fb. Checks:4 WARNING, 8 NOTE, 2 OK. Indexed: no.

TargetResultTimeFilesSyslog
bioc-checksWARNING161
linux-devel-arm64NOTE145
linux-devel-x86_64NOTE160
source / vignettesOK165
linux-release-arm64NOTE154
linux-release-x86_64NOTE154
macos-release-arm64NOTE101
macos-release-x86_64NOTE280
macos-oldrel-arm64NOTE114
macos-oldrel-x86_64NOTE300
windows-develWARNING121
windows-releaseWARNING106
windows-oldrelWARNING169
wasm-releaseOK109

Exports:AICBICcsubsetcvdmngroupdmndmngroupfittedgoodnessOfFitheatmapdmnlaplacemixturemixturewtpredictrocshowsummary

Dependencies:BiocGenericsgenericsIRangesS4Vectors

DirichletMultinomial for Clustering and Classification of Microbiome Data

Martin Morgan

Rendered fromDirichletMultinomial.Rmdusingknitr::rmarkdownon Jun 06 2026.

Last update: 2024-10-19
Started: 2024-10-19

Readme and manuals

Help Manual

Help pageTopics
Dirichlet-Multinomial Mixture Model Machine Learning for Microbiome DataDirichletMultinomial-package
Cross-validation on Dirichlet-Multinomial classifiers.cvdmngroup
Data objects used for examples and the vignettebestgrp fit xval
Fit Dirichlet-Multinomial models to count data.dmn
Class '"DMN"'DMN-class
Dirichlet-Multinomial generative classifiers.dmngroup
Class '"DMNGroup"'DMNGroup-class
Heatmap representation of samples assigned to Dirichlet components.heatmapdmn
Access model components.AIC,DMN-method BIC,DMN-method fitted,DMN-method fitted,DMNGroup-method goodnessOfFit laplace mixture mixturewt predict,DMN-method predict,DMNGroup-method show,DMN-method show,DMNGroup-method summary,DMNGroup-method
Summarize receiver-operator characteristicsroc
Helpful utility functionscsubset