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A Hidden Markov Model Approach for Identifying Differentially Methylated Sites and Regions for Beta-Valued DNA Methylation Data

Bioconductor version: Release (3.19)

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] , Romina Silva [aut], Antoinette Sabrina Perry [aut], Ronald William Watson [aut], Isobel Claire Gorley [aut] , Thomas Brendan Murphy [aut] , Florence Jaffrezic [aut], Andrea Rau [aut]

Maintainer: Koyel Majumdar <koyel.majumdar at>

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biocViews BiomedicalInformatics, Coverage, DNAMethylation, DifferentialMethylation, GeneTarget, HiddenMarkovModel, ImmunoOncology, MethylationArray, Microarray, MultipleComparison, Sequencing, Software, Spatial
Version 1.0.0
In Bioconductor since BioC 3.19 (R-4.4) (< 6 months)
License GPL-3
Depends R (>= 4.3.0), SummarizedExperiment, S4Vectors, GenomicRanges
Imports stats, ggplot2, scales, methods, pROC, foreach, doParallel, parallel, cowplot, dplyr, tidyr, tidyselect, stringr, utils
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