recipe bioconductor-fenr

Fast functional enrichment for interactive applications






Perform fast functional enrichment on feature lists (like genes or proteins) using the hypergeometric distribution. Tailored for speed, this package is ideal for interactive platforms such as Shiny. It supports the retrieval of functional data from sources like GO, KEGG, Reactome, and WikiPathways. By downloading and preparing data first, it allows for rapid successive tests on various feature selections without the need for repetitive, time-consuming preparatory steps typical of other packages.

package bioconductor-fenr

(downloads) docker_bioconductor-fenr



depends bioconductor-biocfilecache:


depends bioconductor-biomart:


depends r-assertthat:

depends r-base:


depends r-dplyr:

depends r-ggplot2:

depends r-httr:

depends r-jsonlite:

depends r-progress:

depends r-purrr:

depends r-readr:

depends r-rlang:

depends r-shiny:

depends r-stringr:

depends r-tibble:

depends r-tidyr:

depends r-tidyselect:

depends r-xml:



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-fenr

and update with::

   mamba update bioconductor-fenr

To create a new environment, run:

mamba create --name myenvname bioconductor-fenr

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

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