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]|
|Bioconductor views||Bayesian Clustering Coverage DNAMethylation Epigenetics FeatureExtraction GeneExpression GeneRegulation Genetics KEGG RNASeq Regression Sequencing|
|Maintainer||Chantriolnt-Andreas Kapourani <[email protected]>|
|Package repository||View on GitHub|
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