recipe bioconductor-methylgsa

Gene Set Analysis Using the Outcome of Differential Methylation






The main functions for methylGSA are methylglm and methylRRA. methylGSA implements logistic regression adjusting number of probes as a covariate. methylRRA adjusts multiple p-values of each gene by Robust Rank Aggregation. For more detailed help information, please see the vignette.

package bioconductor-methylgsa

(downloads) docker_bioconductor-methylgsa



depends bioconductor-annotationdbi:


depends bioconductor-biocparallel:


depends bioconductor-clusterprofiler:


depends bioconductor-go.db:


depends bioconductor-illuminahumanmethylation450kanno.ilmn12.hg19:


depends bioconductor-illuminahumanmethylationepicanno.ilm10b4.hg19:


depends bioconductor-missmethyl:




depends bioconductor-reactome.db:


depends r-base:


depends r-ggplot2:

depends r-robustrankaggreg:

depends r-shiny:

depends r-stringr:



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-methylgsa

and update with::

   mamba update bioconductor-methylgsa

To create a new environment, run:

mamba create --name myenvname bioconductor-methylgsa

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

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