recipe r-empiricalfdr.deseq2

Auxiliary functions for the DESeq2 package to simulate read counts according to the null hypothesis (i.e., with empirical sample size factors, per-gene total counts and dispersions, but without effects of predictor variables) and to compute the empirical false discovery rate.



GPL3 / GPL-3



package r-empiricalfdr.deseq2

(downloads) docker_r-empiricalfdr.deseq2



depends bioconductor-deseq2:

depends bioconductor-genomicranges:

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 r-empiricalfdr.deseq2

and update with::

   mamba update r-empiricalfdr.deseq2

To create a new environment, run:

mamba create --name myenvname r-empiricalfdr.deseq2

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 `r-empiricalfdr.deseq2/tags`_ for valid values for ``<tag>``)

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