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ramr

This is the development version of ramr; for the stable release version, see ramr.

Detection of Rare Aberrantly Methylated Regions in Array and NGS Data

Bioconductor version: Development (3.18)

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")

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

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")
ramr HTML R Script
Reference Manual PDF
NEWS Text

Details

biocViews DNAMethylation, DifferentialMethylation, Epigenetics, MethylSeq, MethylationArray, Software
Version 1.9.0
In Bioconductor since BioC 3.13 (R-4.1) (2 years)
License Artistic-2.0
Depends R (>= 4.1), GenomicRanges, parallel, doParallel, foreach, doRNG, methods
Imports IRanges, BiocGenerics, ggplot2, reshape2, EnvStats, ExtDist, matrixStats, S4Vectors
Linking To
Suggests RUnit, knitr, rmarkdown, gridExtra, annotatr, LOLA, org.Hs.eg.db, TxDb.Hsapiens.UCSC.hg19.knownGene
System Requirements
Enhances
URL https://github.com/BBCG/ramr
Bug Reports https://github.com/BBCG/ramr/issues
See More
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_1.9.0.tar.gz
Windows Binary ramr_1.9.0.zip
macOS Binary (x86_64) ramr_1.9.0.tgz
macOS Binary (arm64) ramr_1.9.0.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