recipe bioconductor-edger

Empirical Analysis of Digital Gene Expression Data in R



GPL (>=2)




biotools: edger, usegalaxy-eu: edger

Differential expression analysis of RNA-seq expression profiles with biological replication. Implements a range of statistical methodology based on the negative binomial distributions, including empirical Bayes estimation, exact tests, generalized linear models and quasi-likelihood tests. As well as RNA-seq, it be applied to differential signal analysis of other types of genomic data that produce read counts, including ChIP-seq, ATAC-seq, Bisulfite-seq, SAGE and CAGE.

package bioconductor-edger

(downloads) docker_bioconductor-edger



depends bioconductor-limma:


depends libblas:


depends libgcc-ng:


depends liblapack:


depends libstdcxx-ng:


depends r-base:


depends r-locfit:

depends r-rcpp:



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-edger

and update with::

   mamba update bioconductor-edger

To create a new environment, run:

mamba create --name myenvname bioconductor-edger

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

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