BPRMeth

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

Model higher-order methylation profiles


Bioconductor version: Development (3.21)

The BPRMeth package is a probabilistic method to quantify explicit features of methylation profiles, in a way that would make it easier to formally use such profiles in downstream modelling efforts, such as predicting gene expression levels or clustering genomic regions or cells according to their methylation profiles.

Author: Chantriolnt-Andreas Kapourani [aut, cre]

Maintainer: Chantriolnt-Andreas Kapourani <kapouranis.andreas at gmail.com>

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

Installation

To install this package, start R (version "4.5") and enter:


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

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

BiocManager::install("BPRMeth")

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("BPRMeth")
BPRMeth: Model higher-order methylation profiles HTML R Script
Reference Manual PDF
NEWS Text
LICENSE Text

Details

biocViews Bayesian, Clustering, Coverage, DNAMethylation, Epigenetics, FeatureExtraction, GeneExpression, GeneRegulation, Genetics, ImmunoOncology, KEGG, RNASeq, Regression, Sequencing, SingleCell, Software
Version 1.33.0
In Bioconductor since BioC 3.4 (R-3.3) (8 years)
License GPL-3 | file LICENSE
Depends R (>= 3.5.0), GenomicRanges
Imports assertthat, methods, MASS, doParallel, parallel, e1071, earth, foreach, randomForest, stats, IRanges, S4Vectors, data.table, graphics, truncnorm, mvtnorm, Rcpp (>= 0.12.14), matrixcalc, magrittr, kernlab, ggplot2, cowplot, BiocStyle
System Requirements
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Suggests testthat, knitr, rmarkdown
Linking To Rcpp, RcppArmadillo
Enhances
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Build Report Build Report

Package Archives

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

Source Package BPRMeth_1.33.0.tar.gz
Windows Binary (x86_64) BPRMeth_1.33.0.zip
macOS Binary (x86_64) BPRMeth_1.33.0.tgz
macOS Binary (arm64)
Source Repository git clone https://git.bioconductor.org/packages/BPRMeth
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/BPRMeth
Bioc Package Browser https://code.bioconductor.org/browse/BPRMeth/
Package Short Url https://bioconductor.org/packages/BPRMeth/
Package Downloads Report Download Stats