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DirichletMultinomial (version 1.14.0)

Dirichlet-Multinomial Mixture Model Machine Learning for Microbiome Data

Description

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 This package is an interface to code originally made available by Holmes, Harris, and Quince, 2012, PLoS ONE 7(2): 1-15, as discussed further in the man page for this package, ?DirichletMultinomial.

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Version

Version

1.14.0

License

LGPL-3

Maintainer

Martin Morgan

Last Published

February 15th, 2017

Functions in DirichletMultinomial (1.14.0)

dmngroup

Dirichlet-Multinomial generative classifiers.
data

Data objects used for examples and the vignette
DMN-class

Class "DMN"
cvdmngroup

Cross-validation on Dirichlet-Multinomial classifiers.
DMNGroup-class

Class "DMNGroup"
Utilities

Helpful utility functions
DirichletMultinomial-package

Dirichlet-Multinomial Mixture Model Machine Learning for Microbiome Data
dmn

Fit Dirichlet-Multinomial models to count data.
roc

Summarize receiver-operator characteristics
model components

Access model components.
heatmapdmn

Heatmap representation of samples assigned to Dirichlet components.