recipe bioconductor-compcoder

RNAseq data simulation, differential expression analysis and performance comparison of differential expression methods



GPL (>= 2)



This package provides extensive functionality for comparing results obtained by different methods for differential expression analysis of RNAseq data. It also contains functions for simulating count data. Finally, it provides convenient interfaces to several packages for performing the differential expression analysis. These can also be used as templates for setting up and running a user-defined differential analysis workflow within the framework of the package.

package bioconductor-compcoder

(downloads) docker_bioconductor-compcoder



depends bioconductor-edger:


depends bioconductor-limma:


depends r-ape:

depends r-base:


depends r-catools:

depends r-ggplot2:

depends r-gplots:

depends r-gtools:

depends r-kernsmooth:

depends r-knitr:


depends r-lattice:


depends r-markdown:

depends r-mass:

depends r-matrixstats:

depends r-modeest:

depends r-phylolm:

depends r-rmarkdown:

depends r-rocr:

depends r-shiny:

depends r-shinydashboard:

depends r-sm:

depends r-stringr:

depends r-vioplot:



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-compcoder

and update with::

   mamba update bioconductor-compcoder

To create a new environment, run:

mamba create --name myenvname bioconductor-compcoder

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

Download stats