ramr

DOI: 10.18129/B9.bioc.ramr  

This package is for version 3.17 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: 3.17

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>

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

Installation

To install this package, start R (version "4.3") and enter:

if (!require("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 1.8.0
In Bioconductor since BioC 3.13 (R-4.1) (2.5 years)
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_1.8.0.tar.gz
Windows Binary ramr_1.8.0.zip
macOS Binary (x86_64) ramr_1.8.0.tgz
macOS Binary (arm64) ramr_1.8.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/ramr
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/ramr
Bioc Package Browser https://code.bioconductor.org/browse/ramr/
Package Short Url https://bioconductor.org/packages/ramr/
Package Downloads Report Download Stats

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