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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
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Model higher-order methylation profiles
Bioconductor version: Release (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")
| R Script | An Introduction to the BPR method | |
| 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 |
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