recipe bioconductor-dirichletmultinomial

Dirichlet-Multinomial Mixture Model Machine Learning for Microbiome Data

Homepage:

https://bioconductor.org/packages/3.18/bioc/html/DirichletMultinomial.html

License:

LGPL-3.0-only

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 This package is an interface to code originally made available by Holmes, Harris, and Quince, 2012, PLoS ONE 7(2): 1-15, as discussed further in the man page for this package, ?DirichletMultinomial.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

(downloads) docker_bioconductor-dirichletmultinomial

versions:
1.44.0-1,  1.44.0-0,  1.42.0-0,  1.40.0-1,  1.40.0-0,  1.36.0-3,  1.36.0-2,  1.36.0-1,  1.36.0-0, 

1.44.0-1,  1.44.0-0,  1.42.0-0,  1.40.0-1,  1.40.0-0,  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:

>=0.48.0,<0.49.0

depends bioconductor-biocgenerics:

>=0.48.1,<0.49.0a0

depends bioconductor-iranges:

>=2.36.0,<2.37.0

depends bioconductor-iranges:

>=2.36.0,<2.37.0a0

depends bioconductor-s4vectors:

>=0.40.0,<0.41.0

depends bioconductor-s4vectors:

>=0.40.2,<0.41.0a0

depends gsl:

>=2.7,<2.8.0a0

depends libblas:

>=3.9.0,<4.0a0

depends libgcc-ng:

>=12

depends liblapack:

>=3.9.0,<4.0a0

depends r-base:

>=4.3,<4.4.0a0

requirements:

Installation

You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).

While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.

Given that you already have a conda environment in which you want to have this package, install with:

   mamba install bioconductor-dirichletmultinomial

and update with::

   mamba update bioconductor-dirichletmultinomial

To create a new environment, run:

mamba create --name myenvname bioconductor-dirichletmultinomial

with myenvname being a reasonable name for the environment (see e.g. the mamba docs for details and further options).

Alternatively, use the docker container:

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

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

Download stats

Link to this page

Render an install-with-bioconda badge with the following MarkDown:

[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/bioconductor-dirichletmultinomial/README.html)