recipe r-viber

Variational Binomial Mixtures.

Homepage:

https://github.com/caravagnalab/VIBER

Documentation:

https://caravagnalab.github.io/VIBER/

License:

GPL3 / GPL-3.0-or-later

Recipe:

/r-viber/meta.yaml

VIBER is a package that implements a variational Bayesian model to fit multi-variate Binomial mixtures. The statistical model is semi-parametric and fit by a variational mean-field approximation to the model posterior. The components are Binomial distributions which can model count data; these can be used to model sequencing counts in the context of cancer, for instance. The package implements methods to fit and visualize clustering results.

package r-viber

(downloads) docker_r-viber

versions:

1.0.0-0

depends r-base:

>=4.4,<4.5.0a0

depends r-cli:

depends r-crayon:

depends r-ctree:

depends r-dplyr:

depends r-easypar:

depends r-ggplot2:

depends r-pio:

depends r-reshape2:

requirements:

additional platforms:

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 r-viber

and update with::

   mamba update r-viber

To create a new environment, run:

mamba create --name myenvname r-viber

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/r-viber:<tag>

(see `r-viber/tags`_ for valid values for ``<tag>``)

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Link to this page

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