REMP

DOI: 10.18129/B9.bioc.REMP  

This package is for version 3.17 of Bioconductor; for the stable, up-to-date release version, see REMP.

Repetitive Element Methylation Prediction

Bioconductor version: 3.17

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")

 

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

Details

biocViews DNAMethylation, DataImport, DifferentialMethylation, Epigenetics, GenomeWideAssociation, MethylationArray, Microarray, MultiChannel, Preprocessing, QualityControl, Sequencing, Software, TwoChannel
Version 1.24.0
In Bioconductor since BioC 3.5 (R-3.4) (6.5 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
LinkingTo
Suggests IlluminaHumanMethylation450kanno.ilmn12.hg19, IlluminaHumanMethylationEPICanno.ilm10b2.hg19, BSgenome.Hsapiens.UCSC.hg19, BSgenome.Hsapiens.UCSC.hg38, knitr, rmarkdown, minfiDataEPIC
SystemRequirements
Enhances
URL https://github.com/YinanZheng/REMP
BugReports https://github.com/YinanZheng/REMP/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 REMP_1.24.0.tar.gz
Windows Binary REMP_1.24.0.zip
macOS Binary (x86_64) REMP_1.24.0.tgz
macOS Binary (arm64)
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

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