recipe bioconductor-genextender

Optimized Functional Annotation Of ChIP-seq Data



GPL (>= 3)



geneXtendeR optimizes the functional annotation of ChIP-seq peaks by exploring relative differences in annotating ChIP-seq peak sets to variable-length gene bodies. In contrast to prior techniques, geneXtendeR considers peak annotations beyond just the closest gene, allowing users to see peak summary statistics for the first-closest gene, second-closest gene, …, n-closest gene whilst ranking the output according to biologically relevant events and iteratively comparing the fidelity of peak-to-gene overlap across a user-defined range of upstream and downstream extensions on the original boundaries of each gene's coordinates. Since different ChIP-seq peak callers produce different differentially enriched peaks with a large variance in peak length distribution and total peak count, annotating peak lists with their nearest genes can often be a noisy process. As such, the goal of geneXtendeR is to robustly link differentially enriched peaks with their respective genes, thereby aiding experimental follow-up and validation in designing primers for a set of prospective gene candidates during qPCR.

package bioconductor-genextender

(downloads) docker_bioconductor-genextender



depends bioconductor-annotationdbi:


depends bioconductor-annotationdbi:


depends bioconductor-biocstyle:


depends bioconductor-biocstyle:


depends bioconductor-go.db:


depends bioconductor-go.db:






depends bioconductor-rtracklayer:


depends bioconductor-rtracklayer:


depends libblas:


depends libgcc-ng:


depends liblapack:


depends r-base:


depends r-data.table:

depends r-dplyr:

depends r-networkd3:

depends r-rcolorbrewer:

depends r-snowballc:

depends r-tm:

depends r-wordcloud:



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-genextender

and update with::

   mamba update bioconductor-genextender

To create a new environment, run:

mamba create --name myenvname bioconductor-genextender

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

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