RCAS
This package is for version 3.9 of Bioconductor; for the stable, up-to-date release version, see RCAS.
RNA Centric Annotation System
Bioconductor version: 3.9
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("RCAS")
):
Installation
To install this package, start R (version "3.6") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("RCAS")
For older versions of R, please refer to the appropriate Bioconductor release.
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("RCAS")
How to do meta-analysis of multiple samples | HTML | R Script |
Introduction - single sample analysis | HTML | R Script |
Reference Manual | ||
NEWS | Text |
Details
biocViews | Coverage, GO, GeneSetEnrichment, GeneTarget, GenomeAnnotation, MotifAnnotation, MotifDiscovery, Software, Transcriptomics |
Version | 1.10.1 |
In Bioconductor since | BioC 3.4 (R-3.3) (7.5 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 |
System Requirements | pandoc (>= 1.12.3) |
URL |
See More
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 |
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Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
Source Package | RCAS_1.10.1.tar.gz |
Windows Binary | RCAS_1.10.1.zip (64-bit only) |
Mac OS X 10.11 (El Capitan) | RCAS_1.10.1.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/RCAS |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/RCAS |
Bioc Package Browser | https://code.bioconductor.org/browse/RCAS/ |
Package Short Url | https://bioconductor.org/packages/RCAS/ |
Package Downloads Report | Download Stats |
Old Source Packages for BioC 3.9 | Source Archive |