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. RCAS supports all genome versions that are available in
if (!requireNamespace("BiocManager", quietly=TRUE))
Installing the development version from Github
Installing via Bioconda channel
conda install bioconductor-rcas -c bioconda
Installing via Guix
guix package -i r r-rcas
Package vignettes and reference manual
For detailed instructions on how to use RCAS, please see:
- package vignette for single sample analysis
- package vignette for multi-sample analysis
- reference manual for more information about the detailed functions available in RCAS.
Use cases from published RNA-based omics datasets
Multi-sample analysis use case
- See an example report comparing the peak regions discovered via CLIP-sequencing experiments of the RNA-binding protein FUS by Nakaya et al, 2013, Synaptic Functional Regulator FMR1 by Ascano et al. 2012, and Eukaryotic initiation factor 4A-III by Sauliere et al, 2012.
Single Sample Analysis Use Cases
- input: PARCLIP_QKI_Hafner2010c_hg19
- input: human_FANTOM4_tiRNAs.bed
- input: GSE70485_human_peaks.txt.gz
In order to cite RCAS, please use:
Bora Uyar, Dilmurat Yusuf, Ricardo Wurmus, Nikolaus Rajewsky, Uwe Ohler, Altuna Akalin; RCAS: an RNA centric annotation system for transcriptome-wide regions of interest. Nucleic Acids Res 2017 gkx120. doi: 10.1093/nar/gkx120
See our publication here.
RCAS is developed in the group of Altuna Akalin (head of the Scientific Bioinformatics Platform) by Bora Uyar (Bioinformatics Scientist), Dilmurat Yusuf (Bioinformatics Scientist) and Ricardo Wurmus (System Administrator) at the Berlin Institute of Medical Systems Biology (BIMSB) at the Max-Delbrueck-Center for Molecular Medicine (MDC) in Berlin.