recipe bioconductor-fgga

Hierarchical ensemble method based on factor graph






Package that implements the FGGA algorithm. This package provides a hierarchical ensemble method based ob factor graphs for the consistent cross-ontology annotation of protein coding genes. FGGA embodies elements of predicate logic, communication theory, supervised learning and inference in graphical models.

package bioconductor-fgga

(downloads) docker_bioconductor-fgga



depends bioconductor-biocfilecache:


depends bioconductor-graph:


depends bioconductor-rbgl:


depends r-base:


depends r-curl:

depends r-e1071:

depends r-grbase:

depends r-jsonlite:



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-fgga

and update with::

   mamba update bioconductor-fgga

To create a new environment, run:

mamba create --name myenvname bioconductor-fgga

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

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