RCAS project

Introduction

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 of annotated gene sets, GO terms, and de novo motif discovery. RCAS is available in the Bioconductor repository, packaged in multiple environments including Conda, Galaxy, and Guix, and as a webservice at http://rcas.mdc-berlin.de/.

Currently supported genome builds are hg19 and hg38 (human), mm9 and mm10 (mouse), dm3 (fly), and ce10 (worm). Modules for annotation summaries and motif analysis are supported for each of these genome builds. GO term and gene-set enrichment analyses are supported for hg19, hg38, mm9, mm10, and dm3. ce10 is currently not supportedfor GO/GSEA modules.

installation:

Installing from Bioconductor

source('http://bioconductor.org/biocLite.R')

biocLite('RCAS')

Installing the development version from Github

library('devtools')
devtools::install_github('BIMSBbioinfo/RCAS')

Installing via Bioconda channel

conda install bioconductor-rcas -c bioconda

Installing via Guix

guix package -i r r-rcas

usage:

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

• The reference files needed for reproducing the reports below:

  • Homo_sapiens.GRCh37.75.gtf.gz
  • c2.all.v5.1.entrez.gmt

• RCAS report for PUM2 RNA-binding sites detected by PAR-CLIP technique (Hafner et al, 2010)

  • input: PARCLIP_PUM2_Hafner2010b_hg19

• RCAS report for QKI RNA-binding sites detected by PAR-CLIP technique (Hafner et al, 2010)

  • input: PARCLIP_QKI_Hafner2010c_hg19

• RCAS report for IGF2BP123 RNA-binding sites detected by PAR-CLIP technique (Hafner et al, 2010)

  • input: PARCLIP_IGF2BP123_Hafner2010d_hg19

• RCAS report for tiny RNA (tiRNA) loci detected by deepCAGE analysis (Taft et al. 2009)

  • input: human_FANTOM4_tiRNAs.bed

• RCAS report for m¹A methylation sites (Dominissini et al, 2016)

  • input: GSE70485_human_peaks.txt.gz

Citation

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.

Acknowledgements

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.

RCAS is developed as a bioinformatics service as part of the RNA Bioinformatics Center, which is one of the eight centers of the German Network for Bioinformatics Infrastructure (de.NBI).