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REMP

Repetitive Element Methylation Prediction


Bioconductor version: Release (3.18)

Machine learning-based tools to predict DNA methylation of locus-specific repetitive elements (RE) by learning surrounding genetic and epigenetic information. These tools provide genomewide and single-base resolution of DNA methylation prediction on RE that are difficult to measure using array-based or sequencing-based platforms, which enables epigenome-wide association study (EWAS) and differentially methylated region (DMR) analysis on RE.

Author: Yinan Zheng [aut, cre], Lei Liu [aut], Wei Zhang [aut], Warren Kibbe [aut], Lifang Hou [aut, cph]

Maintainer: Yinan Zheng <y-zheng at northwestern.edu>

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

Installation

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


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

BiocManager::install("REMP")

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("REMP")
An Introduction to the REMP Package PDF R Script
Reference Manual PDF
NEWS Text

Details

biocViews DNAMethylation, DataImport, DifferentialMethylation, Epigenetics, GenomeWideAssociation, MethylationArray, Microarray, MultiChannel, Preprocessing, QualityControl, Sequencing, Software, TwoChannel
Version 1.26.0
In Bioconductor since BioC 3.5 (R-3.4) (7 years)
License GPL-3
Depends R (>= 3.6), SummarizedExperiment(>= 1.1.6), minfi(>= 1.22.0)
Imports readr, rtracklayer, graphics, stats, utils, methods, settings, BiocGenerics, S4Vectors, Biostrings, GenomicRanges, IRanges, GenomeInfoDb, BiocParallel, doParallel, parallel, foreach, caret, kernlab, ranger, BSgenome, AnnotationHub, org.Hs.eg.db, impute, iterators
System Requirements
URL https://github.com/YinanZheng/REMP
Bug Reports https://github.com/YinanZheng/REMP/issues
See More
Suggests IlluminaHumanMethylation450kanno.ilmn12.hg19, IlluminaHumanMethylationEPICanno.ilm10b2.hg19, BSgenome.Hsapiens.UCSC.hg19, BSgenome.Hsapiens.UCSC.hg38, knitr, rmarkdown, minfiDataEPIC
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Package Archives

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

Source Package REMP_1.26.0.tar.gz
Windows Binary REMP_1.26.0.zip
macOS Binary (x86_64) REMP_1.26.0.tgz
macOS Binary (arm64) REMP_1.26.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/REMP
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/REMP
Bioc Package Browser https://code.bioconductor.org/browse/REMP/
Package Short Url https://bioconductor.org/packages/REMP/
Package Downloads Report Download Stats