Package: DirichletMultinomial 1.49.0

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 This package is an interface to code originally made available by Holmes, Harris, and Quince, 2012, PLoS ONE 7(2): 1-15, as discussed further in the man page for this package, ?DirichletMultinomial.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

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DirichletMultinomial.pdf |DirichletMultinomial.html
DirichletMultinomial/json (API)

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

Peer review:

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

Pkgdown: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-1.49.0(bioc 3.21)DirichletMultinomial-1.48.0(bioc 3.20)

immunooncologymicrobiomesequencingclusteringclassificationmetagenomicsgsl

10.97 score 11 stars 25 packages 125 scripts 9.5k downloads 9 mentions 16 exports 4 dependencies

Last updated 2 months agofrom:776fd59c4b. Checks:OK: 1 NOTE: 5 WARNING: 3. Indexed: yes.

TargetResultDate
Doc / VignettesOKDec 19 2024
R-4.5-win-x86_64WARNINGDec 19 2024
R-4.5-linux-x86_64NOTEDec 19 2024
R-4.4-win-x86_64WARNINGDec 19 2024
R-4.4-mac-x86_64NOTEDec 19 2024
R-4.4-mac-aarch64NOTEDec 19 2024
R-4.3-win-x86_64WARNINGDec 19 2024
R-4.3-mac-x86_64NOTEDec 19 2024
R-4.3-mac-aarch64NOTEDec 19 2024

Exports:AICBICcsubsetcvdmngroupdmndmngroupfittedgoodnessOfFitheatmapdmnlaplacemixturemixturewtpredictrocshowsummary

Dependencies:BiocGenericsgenericsIRangesS4Vectors

DirichletMultinomial for Clustering and Classification of Microbiome Data

Rendered fromDirichletMultinomial.Rmdusingknitr::rmarkdownon Dec 19 2024.

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