recipe bioconductor-epidecoder

epidecodeR: a functional exploration tool for epigenetic and epitranscriptomic regulation






epidecodeR is a package capable of analysing impact of degree of DNA/RNA epigenetic chemical modifications on dysregulation of genes or proteins. This package integrates chemical modification data generated from a host of epigenomic or epitranscriptomic techniques such as ChIP-seq, ATAC-seq, m6A-seq, etc. and dysregulated gene lists in the form of differential gene expression, ribosome occupancy or differential protein translation and identify impact of dysregulation of genes caused due to varying degrees of chemical modifications associated with the genes. epidecodeR generates cumulative distribution function (CDF) plots showing shifts in trend of overall log2FC between genes divided into groups based on the degree of modification associated with the genes. The tool also tests for significance of difference in log2FC between groups of genes.

package bioconductor-epidecoder

(downloads) docker_bioconductor-epidecoder



depends bioconductor-genomicranges:


depends bioconductor-iranges:


depends bioconductor-rtracklayer:


depends r-base:


depends r-dplyr:

depends r-envstats:

depends r-ggplot2:

depends r-ggpubr:

depends r-rstatix:



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-epidecoder

and update with::

   mamba update bioconductor-epidecoder

To create a new environment, run:

mamba create --name myenvname bioconductor-epidecoder

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

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