DirichletMultinomial-package: Dirichlet-Multinomial Mixture Model Machine Learning for...
In DirichletMultinomial: 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interface to code originally made available by Holmes, Harris, and
Qunice, 2012, PLoS ONE 7(2): 1-15.
Details
The estimation routine is from the LGPL-licensed (as stated on the
corresponding googlecode page) source
http://microbedmm.googlecode.com/files/MicrobeDMMv1.0.tar.gz,
retrieved 17 Feburary 2012.
The algorithm is described in Holmes I, Harris K, Quince C, 2012
Dirichlet Multinomial Mixtures: Generative Models for Microbial
Metagenomics. PLoS ONE 7(2): e30126. doi:10.1371/journal.pone.0030126.
Author(s)
Maintainer: Martin Morgan mailto:mtmorgan@fhcrc.org
DirichletMultinomial documentation built on Nov. 8, 2020, 7 p.m.
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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 This package is an interface to code originally made available by Holmes, Harris, and Qunice, 2012, PLoS ONE 7(2): 1-15.
Details
The estimation routine is from the LGPL-licensed (as stated on the corresponding googlecode page) source http://microbedmm.googlecode.com/files/MicrobeDMMv1.0.tar.gz, retrieved 17 Feburary 2012.
The algorithm is described in Holmes I, Harris K, Quince C, 2012 Dirichlet Multinomial Mixtures: Generative Models for Microbial Metagenomics. PLoS ONE 7(2): e30126. doi:10.1371/journal.pone.0030126.
Author(s)
Maintainer: Martin Morgan mailto:mtmorgan@fhcrc.org
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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