This is the released version of betaHMM; for the devel version, see betaHMM.
A Hidden Markov Model Approach for Identifying Differentially Methylated Sites and Regions for Beta-Valued DNA Methylation DataBioconductor version: Release (3.21)
A novel approach utilizing a homogeneous hidden Markov model. And effectively model untransformed beta values. To identify DMCs while considering the spatial. Correlation of the adjacent CpG sites.
Author: Koyel Majumdar [cre, aut] ORCID: 0000-0001-6469-488X , Romina Silva [aut], Antoinette Sabrina Perry [aut], Ronald William Watson [aut], Isobel Claire Gorley [aut] ORCID: 0000-0001-7713-681X , Thomas Brendan Murphy [aut] ORCID: 0000-0002-5668-7046 , Florence Jaffrezic [aut], Andrea Rau [aut] ORCID: 0000-0001-6469-488X
Maintainer: Koyel Majumdar <koyel.majumdar at ucdconnect.ie>
Citation (from within R, entercitation("betaHMM")): Installation
To install this package, start R (version "4.5") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("betaHMM")
For older versions of R, please refer to the appropriate Bioconductor release.
DocumentationTo view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("betaHMM")Follow Installation instructions to use this package in your R session.
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