recipe bioconductor-dirichletmultinomial

Dirichlet-Multinomial Mixture Model Machine Learning for Microbiome Data

Homepage:

https://bioconductor.org/packages/3.14/bioc/html/DirichletMultinomial.html

License:

LGPL-3

Recipe:

/bioconductor-dirichletmultinomial/meta.yaml

Links:

biotools: dirichletmultinomial, doi: 10.1371/journal.pone.0030126

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 This package is an interface to code originally made available by Holmes, Harris, and Quince, 2012, PLoS ONE 7(2): 1-15, as discussed further in the man page for this package, ?DirichletMultinomial.

package bioconductor-dirichletmultinomial

Versions:

1.36.0-3,  1.36.0-2,  1.36.0-1,  1.36.0-0,  1.34.0-0,  1.32.0-1,  1.32.0-0,  1.30.0-0,  1.28.0-0, 

1.36.0-3,  1.36.0-2,  1.36.0-1,  1.36.0-0,  1.34.0-0,  1.32.0-1,  1.32.0-0,  1.30.0-0,  1.28.0-0,  1.26.0-1,  1.24.1-0,  1.24.0-0,  1.22.0-0,  1.20.0-0,  1.18.0-0,  1.16.0-0

Depends:

• bioconductor-biocgenerics >=0.40.0,<0.41.0

• bioconductor-iranges >=2.28.0,<2.29.0

• bioconductor-s4vectors >=0.32.0,<0.33.0

• gsl >=2.7,<2.8.0a0

• libblas >=3.9.0,<4.0a0

• libgcc-ng >=12

• liblapack >=3.9.0,<4.0a0

• r-base >=4.1,<4.2.0a0

Required By:

• bioconductor-miaviz

• bioconductor-mia

• bioconductor-tfbstools

Installation

With an activated Bioconda channel (see set-up-channels), install with:

conda install bioconductor-dirichletmultinomial

and update with:

conda update bioconductor-dirichletmultinomial

or use the docker container:

docker pull quay.io/biocontainers/bioconductor-dirichletmultinomial:<tag>

(see bioconductor-dirichletmultinomial/tags for valid values for <tag>)

Download stats

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