recipe bioconductor-iterativebma

The Iterative Bayesian Model Averaging (BMA) algorithm



GPL (>= 2)




biotools: iterativebma, doi: 10.1186/gb-2008-9-7-r118

The iterative Bayesian Model Averaging (BMA) algorithm is a variable selection and classification algorithm with an application of classifying 2-class microarray samples, as described in Yeung, Bumgarner and Raftery (Bioinformatics 2005, 21: 2394-2402).

package bioconductor-iterativebma

(downloads) docker_bioconductor-iterativebma



depends bioconductor-biobase:


depends r-base:


depends r-bma:

depends r-leaps:



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-iterativebma

and update with::

   mamba update bioconductor-iterativebma

To create a new environment, run:

mamba create --name myenvname bioconductor-iterativebma

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<tag>

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

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