recipe bioconductor-fabia

FABIA: Factor Analysis for Bicluster Acquisition



LGPL (>= 2.1)




biotools: fabia

Biclustering by "Factor Analysis for Bicluster Acquisition" (FABIA). FABIA is a model-based technique for biclustering, that is clustering rows and columns simultaneously. Biclusters are found by factor analysis where both the factors and the loading matrix are sparse. FABIA is a multiplicative model that extracts linear dependencies between samples and feature patterns. It captures realistic non-Gaussian data distributions with heavy tails as observed in gene expression measurements. FABIA utilizes well understood model selection techniques like the EM algorithm and variational approaches and is embedded into a Bayesian framework. FABIA ranks biclusters according to their information content and separates spurious biclusters from true biclusters. The code is written in C.

package bioconductor-fabia

(downloads) docker_bioconductor-fabia



depends bioconductor-biobase:


depends bioconductor-biobase:


depends libblas:


depends libgcc-ng:


depends liblapack:


depends r-base:




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-fabia

and update with::

   mamba update bioconductor-fabia

To create a new environment, run:

mamba create --name myenvname bioconductor-fabia

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-fabia/tags`_ for valid values for ``<tag>``)

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