recipe bioconductor-cliprofiler

A package for the CLIP data visualization






An easy and fast way to visualize and profile the high-throughput IP data. This package generates the meta gene profile and other profiles. These profiles could provide valuable information for understanding the IP experiment results.

package bioconductor-cliprofiler

(downloads) docker_bioconductor-cliprofiler



depends bioconductor-biostrings:


depends bioconductor-bsgenome:


depends bioconductor-genomicranges:


depends bioconductor-rtracklayer:


depends bioconductor-s4vectors:


depends r-base:


depends r-dplyr:

depends r-ggplot2:



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-cliprofiler

and update with::

   mamba update bioconductor-cliprofiler

To create a new environment, run:

mamba create --name myenvname bioconductor-cliprofiler

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

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