Data | Clustering | Generative classifier
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 This package is an interface to code originally made available by Holmes, Harris, and Quince, 2012, PLoS ONE 7(2): 1-15, as discussed further in the man page for this package, ?DirichletMultinomial.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:
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✨
DESCRIPTION
card.svg |card.png
DirichletMultinomial/json (API)
| # Install 'DirichletMultinomial' in R: |
| install.packages('DirichletMultinomial', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/mtmorgan/dirichletmultinomial/issues
Pkgdown/docs site:https://mtmorgan.github.io
Datasets:
On BioConductor:DirichletMultinomial-1.55.0(bioc 3.24)DirichletMultinomial-1.54.0(bioc 3.23)
immunooncologymicrobiomesequencingclusteringclassificationmetagenomicsgsl
Last updated from:15e0e5b4fb. Checks:4 WARNING, 8 NOTE, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| bioc-checks | WARNING | 167 | ||
| linux-devel-arm64 | NOTE | 184 | ||
| linux-devel-x86_64 | NOTE | 214 | ||
| source / vignettes | OK | 200 | ||
| linux-release-arm64 | NOTE | 168 | ||
| linux-release-x86_64 | NOTE | 207 | ||
| macos-release-arm64 | NOTE | 142 | ||
| macos-release-x86_64 | NOTE | 286 | ||
| macos-oldrel-arm64 | NOTE | 113 | ||
| macos-oldrel-x86_64 | NOTE | 279 | ||
| windows-devel | WARNING | 147 | ||
| windows-release | WARNING | 157 | ||
| windows-oldrel | WARNING | 120 | ||
| wasm-release | OK | 186 |
Exports:AICBICcsubsetcvdmngroupdmndmngroupfittedgoodnessOfFitheatmapdmnlaplacemixturemixturewtpredictrocshowsummary
Dependencies:BiocGenericsgenericsIRangesS4Vectors
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Dirichlet-Multinomial Mixture Model Machine Learning for Microbiome Data | DirichletMultinomial-package |
| Cross-validation on Dirichlet-Multinomial classifiers. | cvdmngroup |
| Data objects used for examples and the vignette | bestgrp 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 characteristics | roc |
| Helpful utility functions | csubset |
