recipe bioconductor-vbmp

Variational Bayesian Multinomial Probit Regression

Homepage:

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

License:

GPL (>= 2)

Recipe:

/bioconductor-vbmp/meta.yaml

Links:

biotools: vbmp, doi: 10.1093/bioinformatics/btm535

Variational Bayesian Multinomial Probit Regression with Gaussian Process Priors. It estimates class membership posterior probability employing variational and sparse approximation to the full posterior. This software also incorporates feature weighting by means of Automatic Relevance Determination.

package bioconductor-vbmp

(downloads) docker_bioconductor-vbmp

versions:
1.70.0-01.68.0-01.66.0-01.62.0-01.60.0-01.58.0-11.58.0-01.56.0-01.54.0-0

1.70.0-01.68.0-01.66.0-01.62.0-01.60.0-01.58.0-11.58.0-01.56.0-01.54.0-01.52.0-11.52.0-01.50.0-01.48.0-01.46.0-01.44.0-0

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-vbmp

and update with::

   mamba update bioconductor-vbmp

To create a new environment, run:

mamba create --name myenvname bioconductor-vbmp

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-vbmp:<tag>

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

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