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This is the development version of REMP; for the stable release version, see REMP.
Bioconductor version: Development (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")
):
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("REMP")
For older versions of R, please refer to the appropriate Bioconductor release.
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("REMP")
R Script | An Introduction to the REMP Package | |
Reference Manual |
biocViews | DNAMethylation, DataImport, DifferentialMethylation, Epigenetics, GenomeWideAssociation, MethylationArray, Microarray, MultiChannel, Preprocessing, QualityControl, Sequencing, Software, TwoChannel |
Version | 1.23.0 |
In Bioconductor since | BioC 3.5 (R-3.4) (5.5 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 |
Follow Installation instructions to use this package in your R session.
Source Package | REMP_1.23.0.tar.gz |
Windows Binary | |
macOS Binary (x86_64) | |
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 |
Package Short Url | https://bioconductor.org/packages/REMP/ |
Package Downloads Report | Download Stats |
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