To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("BPRMeth")

In most cases, you don't need to download the package archive at all.

BPRMeth

This package is for version 3.4 of Bioconductor; for the stable, up-to-date release version, see BPRMeth.

Model higher-order methylation profiles

Bioconductor version: 3.4

BPRMeth package uses the Binomial Probit Regression likelihood to model methylation profiles and extract higher order features. These features quantitate precisely notions of shape of a methylation profile. Using these higher order features across promoter-proximal regions, we construct a powerful predictor of gene expression. Also, these features are used to cluster proximal-promoter regions using the EM algorithm.

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 and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("BPRMeth")

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("BPRMeth")

PDF	R Script	An Introduction to the BPR method
PDF		Reference Manual
Text		NEWS

Details

biocViews	Bayesian, Clustering, Coverage, DNAMethylation, Epigenetics, FeatureExtraction, GeneExpression, GeneRegulation, Genetics, KEGG, RNASeq, Regression, Sequencing, Software
Version	1.0.0
In Bioconductor since	BioC 3.4 (R-3.3) (0.5 years)
License	GPL-3
Depends	R (>= 3.3.0), GenomicRanges
Imports	assertthat, methods, MASS, doParallel, parallel, e1071, earth, foreach, randomForest, stats, IRanges, S4Vectors, data.table, graphics
LinkingTo
Suggests	testthat, knitr, rmarkdown, BiocStyle
SystemRequirements
Enhances
URL
Depends On Me
Imports Me
Suggests Me
Build Report

Package Archives

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

Package Source	BPRMeth_1.0.0.tar.gz
Windows Binary	BPRMeth_1.0.0.zip
Mac OS X 10.9 (Mavericks)	BPRMeth_1.0.0.tgz
Subversion source	(username/password: readonly)
Git source	https://github.com/Bioconductor-mirror/BPRMeth/tree/release-3.4
Package Short Url	http://bioconductor.org/packages/BPRMeth/
Package Downloads Report	Download Stats

Documentation »

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