ramr
This is the released version of ramr; for the devel version, see ramr.
Detection of Rare Aberrantly Methylated Regions in Array and NGS Data
Bioconductor version: Release (3.20)
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("ramr")):
Installation
To install this package, start R (version "4.4") 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")| ramr | HTML | R Script |
| Reference Manual | ||
| NEWS | Text |
Details
| biocViews | DNAMethylation, DifferentialMethylation, Epigenetics, MethylSeq, MethylationArray, Software |
| Version | 1.14.0 |
| In Bioconductor since | BioC 3.13 (R-4.1) (3.5 years) |
| License | Artistic-2.0 |
| Depends | R (>= 4.1), GenomicRanges, parallel, doParallel, foreach, doRNG, methods |
| Imports | IRanges, BiocGenerics, ggplot2, reshape2, EnvStats, ExtDist, matrixStats, S4Vectors |
| System Requirements | |
| URL | https://github.com/BBCG/ramr |
| Bug Reports | https://github.com/BBCG/ramr/issues |
See More
| Suggests | RUnit, knitr, rmarkdown, gridExtra, annotatr, LOLA, org.Hs.eg.db, TxDb.Hsapiens.UCSC.hg19.knownGene |
| Linking To | |
| Enhances | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Links To Me | |
| Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | ramr_1.14.0.tar.gz |
| Windows Binary (x86_64) | ramr_1.14.0.zip |
| macOS Binary (x86_64) | ramr_1.14.0.tgz |
| macOS Binary (arm64) | ramr_1.14.0.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 |