recipe bioconductor-rcas

RNA Centric Annotation System







biotools: rcas

RCAS is an R/Bioconductor package designed as a generic reporting tool for the functional analysis of transcriptome-wide regions of interest detected by high-throughput experiments. Such transcriptomic regions could be, for instance, signal peaks detected by CLIP-Seq analysis for protein-RNA interaction sites, RNA modification sites (alias the epitranscriptome), CAGE-tag locations, or any other collection of query regions at the level of the transcriptome. RCAS produces in-depth annotation summaries and coverage profiles based on the distribution of the query regions with respect to transcript features (exons, introns, 5'/3' UTR regions, exon-intron boundaries, promoter regions). Moreover, RCAS can carry out functional enrichment analyses and discriminative motif discovery.

package bioconductor-rcas

(downloads) docker_bioconductor-rcas



depends bioconductor-biocgenerics:


depends bioconductor-biostrings:


depends bioconductor-bsgenome:


depends bioconductor-bsgenome.hsapiens.ucsc.hg19:


depends bioconductor-genomation:


depends bioconductor-genomeinfodb:


depends bioconductor-genomicfeatures:


depends bioconductor-genomicranges:


depends bioconductor-iranges:


depends bioconductor-rtracklayer:


depends bioconductor-s4vectors:


depends pandoc:


depends r-base:


depends r-cowplot:

depends r-data.table:

depends r-dt:


depends r-ggplot2:

depends r-ggseqlogo:

depends r-gprofiler2:

depends r-knitr:


depends r-pbapply:

depends r-pheatmap:

depends r-plotly:


depends r-plotrix:

depends r-proxy:

depends r-ranger:

depends r-rmarkdown:


depends r-rsqlite:



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-rcas

and update with::

   mamba update bioconductor-rcas

To create a new environment, run:

mamba create --name myenvname bioconductor-rcas

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

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