ramr

DOI: 10.18129/B9.bioc.ramr    

This package is for version 3.13 of Bioconductor; for the stable, up-to-date release version, see ramr.

Detection of Rare Aberrantly Methylated Regions in Array and NGS Data

Bioconductor version: 3.13

ramr is an R package for detection of low-frequency aberrant methylation events in large data sets obtained by methylation profiling using array or high-throughput bisulfite sequencing. In addition, package provides functions to visualize found aberrantly methylated regions (AMRs), to generate sets of all possible regions to be used as reference sets for enrichment analysis, and to generate biologically relevant test data sets for performance evaluation of AMR/DMR search algorithms.

Author: Oleksii Nikolaienko [aut, cre]

Maintainer: Oleksii Nikolaienko <oleksii.nikolaienko at gmail.com>

Installation

To install this package, start R (version "4.1") and enter:

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("ramr")

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("ramr")

 

HTML	R Script	ramr
PDF		Reference Manual
Text		NEWS

Details

biocViews	DNAMethylation, DifferentialMethylation, Epigenetics, MethylSeq, MethylationArray, Software
Version	1.0.3
In Bioconductor since	BioC 3.13 (R-4.1) (< 6 months)
License	Artistic-2.0
Depends	R (>= 4.1), GenomicRanges, parallel, doParallel, foreach, doRNG, methods
Imports	IRanges, BiocGenerics, ggplot2, reshape2, EnvStats, ExtDist, matrixStats, S4Vectors
LinkingTo
Suggests	RUnit, knitr, rmarkdown, gridExtra, annotatr, LOLA, org.Hs.eg.db, TxDb.Hsapiens.UCSC.hg19.knownGene
SystemRequirements
Enhances
URL	https://github.com/BBCG/ramr
BugReports	https://github.com/BBCG/ramr/issues
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report

Package Archives

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

Source Package	ramr_1.0.3.tar.gz
Windows Binary	ramr_1.0.3.zip (32- & 64-bit)
macOS 10.13 (High Sierra)	ramr_1.0.3.tgz
Source Repository	git clone https://git.bioconductor.org/packages/ramr
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/ramr
Package Short Url	https://bioconductor.org/packages/ramr/
Package Downloads Report	Download Stats