DOI: 10.18129/B9.bioc.BPRMeth    

Model higher-order methylation profiles

Bioconductor version: Release (3.6)

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>

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PDF R Script An Introduction to the BPR method
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biocViews Bayesian, Clustering, Coverage, DNAMethylation, Epigenetics, FeatureExtraction, GeneExpression, GeneRegulation, Genetics, KEGG, RNASeq, Regression, Sequencing, Software
Version 1.4.0
In Bioconductor since BioC 3.4 (R-3.3) (1.5 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
Suggests testthat, knitr, rmarkdown, BiocStyle
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Source Package BPRMeth_1.4.0.tar.gz
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