recipe bioconductor-gsbenchmark

Gene Set Benchmark






Benchmarks for Machine Learning Analysis of the Gene Sets. The package contains a list of pathways and gene expression data sets used in "Identifying Tightly Regulated and Variably Expressed Networks by Differential Rank Conservation (DIRAC)" (2010) by Eddy et al.

package bioconductor-gsbenchmark

(downloads) docker_bioconductor-gsbenchmark



depends bioconductor-data-packages:


depends curl:

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-gsbenchmark

and update with::

   mamba update bioconductor-gsbenchmark

To create a new environment, run:

mamba create --name myenvname bioconductor-gsbenchmark

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

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