RCAS

DOI: 10.18129/B9.bioc.RCAS    

RNA Centric Annotation System

Bioconductor version: Release (3.6)

RCAS is an automated system that provides dynamic genome annotations for custom input files that contain transcriptomic regions. Such transcriptomic regions could be, for instance, peak regions detected by CLIP-Seq analysis that detect protein-RNA interactions, RNA modifications (alias the epitranscriptome), CAGE-tag locations, or any other collection of target regions at the level of the transcriptome. RCAS is designed as a reporting tool for the functional analysis of RNA-binding sites detected by high-throughput experiments. It takes as input a BED format file containing the genomic coordinates of the RNA binding sites and a GTF file that contains the genomic annotation features usually provided by publicly available databases such as Ensembl and UCSC. RCAS performs overlap operations between the genomic coordinates of the RNA binding sites and the genomic annotation features and produces in-depth annotation summaries such as the distribution of binding sites with respect to gene features (exons, introns, 5'/3' UTR regions, exon-intron boundaries, promoter regions, and whole transcripts). Moreover, by detecting the collection of targeted transcripts, RCAS can carry out functional annotation tables for enriched gene sets (annotated by the Molecular Signatures Database) and GO terms. As one of the most important questions that arise during protein-RNA interaction analysis; RCAS has a module for detecting sequence motifs enriched in the targeted regions of the transcriptome. A full interactive report in HTML format can be generated that contains interactive figures and tables that are ready for publication purposes.

Author: Bora Uyar [aut, cre], Dilmurat Yusuf [aut], Ricardo Wurmus [aut], Altuna Akalin [aut]

Maintainer: Bora Uyar <bora.uyar at mdc-berlin.de>

Citation (from within R, enter citation("RCAS")):

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("RCAS")

Documentation

HTML R Script How to do meta-analysis of multiple samples
HTML R Script Introduction - single sample analysis
PDF   Reference Manual
Text   NEWS

Details

biocViews Coverage, GO, GeneSetEnrichment, GeneTarget, GenomeAnnotation, MotifAnnotation, MotifDiscovery, Software, Transcriptomics
Version 1.4.4
In Bioconductor since BioC 3.4 (R-3.3) (1.5 years)
License Artistic-2.0
Depends R (>= 3.3.0), plotly (>= 4.5.2), DT (>= 0.2), data.table, topGO, motifRG
Imports biomaRt, AnnotationDbi, GenomicRanges, BSgenome.Hsapiens.UCSC.hg19, GenomeInfoDb(>= 1.12.0), Biostrings, rtracklayer, org.Hs.eg.db, GenomicFeatures, rmarkdown (>= 0.9.5), genomation(>= 1.5.5), knitr (>= 1.12.3), BiocGenerics, S4Vectors, stats, plotrix, pbapply, RSQLite, proxy, DBI, pheatmap, ggplot2, cowplot, ggseqlogo, methods, utils
LinkingTo
Suggests BSgenome.Hsapiens.UCSC.hg38, BSgenome.Mmusculus.UCSC.mm10, BSgenome.Mmusculus.UCSC.mm9, BSgenome.Celegans.UCSC.ce10, BSgenome.Dmelanogaster.UCSC.dm3, org.Mm.eg.db, org.Ce.eg.db, org.Dm.eg.db, testthat, covr
SystemRequirements pandoc (>= 1.12.3)
Enhances
URL
Depends On Me
Imports Me
Suggests Me
Build Report  

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package RCAS_1.4.4.tar.gz
Windows Binary RCAS_1.4.4.zip
Mac OS X 10.11 (El Capitan) RCAS_1.4.4.tgz
Source Repository git clone https://git.bioconductor.org/packages/RCAS
Package Short Url http://bioconductor.org/packages/RCAS/
Package Downloads Report Download Stats
Old Source Packages for BioC 3.6 Source Archive

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