A Family of Beta Mixture Models for Clustering Beta-Valued DNA Methylation Data R package betaclust version 1.0.5 A family of novel beta mixture models (BMMs) has been developed by Majumdar et al. (2022) <doi:10.48550/arXiv.2211.01938> to appositely model the beta-valued cytosine-guanine dinucleotide (CpG) sites, to objectively identify methylation state thresholds and to identify the differentially methylated CpG (DMC) sites using a model-based clustering approach. The family of beta mixture models employs different parameter constraints applicable to different study settings. The EM algorithm is used for parameter estimation, with a novel approximation during the M-step providing tractability and ensuring computational feasibility. Software Depends: R (>= 3.5.0) Imports: foreach, doParallel, stats, utils, ggplot2, plotly, scales, pROC Suggests: rmarkdown, knitr Koyel Majumdar <koyelmajumdar.phdresearch@gmail.com> Comprehensive R Archive Network (CRAN) Koyel Majumdar [aut, cre] (ORCID: <https://orcid.org/0000-0003-4692-9002>), Romina Silva [aut], Antoinette Sabrina Perry [aut], Ronald William Watson [aut], Andrea Rau [aut] (ORCID: <https://orcid.org/0000-0001-6469-488X>), Florence Jaffrezic [aut], Thomas Brendan Murphy [aut] (ORCID: <https://orcid.org/0000-0002-5668-7046>), Isobel Claire Gormley [aut] (ORCID: <https://orcid.org/0000-0001-7713-681X>) GPL-3 2025-09-19 application/tgz https://CRAN.R-project.org/package=betaclust doi:10.32614/CRAN.package.betaclust