betaHMM
A Hidden Markov Model Approach for Identifying Differentially Methylated Sites and Regions for Beta-Valued DNA Methylation Data
Bioconductor version: 3.24 · Package version: 1.9.0
Other Bioconductor versions
devel is the development version; release is the current stable one.
3.24 (devel), 3.23 (release)
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.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("betaHMM")Details
| Maintainer | Koyel Majumdar <koyelmajumdar.phdresearch@gmail.com> |
| Author | Koyel Majumdar [cre, aut] (ORCID: <https://orcid.org/0000-0001-6469-488X>), Romina Silva [aut], Antoinette Sabrina Perry [aut], Ronald William Watson [aut], Isobel Claire Gorley [aut] (ORCID: <https://orcid.org/0000-0001-7713-681X>), Thomas Brendan Murphy [aut] (ORCID: <https://orcid.org/0000-0002-5668-7046>), Florence Jaffrezic [aut], Andrea Rau [aut] (ORCID: <https://orcid.org/0000-0001-6469-488X>) |
| License | GPL-3 |
| Source branch | devel |
| Build report | Bioconductor build system, r-universe |
| biocViews | BiomedicalInformatics, Coverage, DNAMethylation, DifferentialMethylation, GeneTarget, HiddenMarkovModel, ImmunoOncology, MethylationArray, Microarray, MultipleComparison, Sequencing, Software, Spatial |
| Package Short Url | https://bioconductor.org/packages/betaHMM/ |
Citation
From within R, enter citation("betaHMM"):
Koyel Majumdar, Romina Silva, Antoinette Sabrina Perry, Ronald William Watson, Isobel Claire Gorley, Thomas Brendan Murphy, Florence Jaffrezic, Andrea Rau. betaHMM: A Hidden Markov Model Approach for Identifying Differentially Methylated Sites and Regions for Beta-Valued DNA Methylation Data. doi:10.18129/B9.bioc.betaHMM, R package version 1.9.0, https://bioconductor.org/packages/betaHMM.
Generated from the package metadata; it may differ from the package's own citation.
Documentation
Download
Follow the installation instructions to use this package in your R session.
| Source package | betaHMM_1.9.0.tar.gz |
| Windows binary (x86_64) | betaHMM_1.9.0.zip |
| macOS binary (arm64) | betaHMM_1.9.0.tgz |
| macOS binary (x86_64) | betaHMM_1.9.0.tgz |
Dependencies
Depends: R (>= 4.3.0), SummarizedExperiment, S4Vectors, GenomicRanges
Imports: stats, ggplot2, scales, methods, pROC, foreach, doParallel, parallel, cowplot, dplyr, tidyr, tidyselect, stringr, utils
Suggests: rmarkdown, knitr, testthat (>= 3.0.0), BiocStyle