Package: DMCHMM
Type: Package
Title: Differentially Methylated CpG using Hidden Markov Model
Version: 1.33.0
Authors@R: c(person("Farhad", "Shokoohi", role = c("aut", "cre"),
                     email = "shokoohi@icloud.com", comment = c(ORCID = "0000-0002-6224-2609"))
              )
Author: Farhad Shokoohi
Maintainer: Farhad Shokoohi <shokoohi@icloud.com>
Description: A pipeline for identifying differentially methylated CpG
        sites using Hidden Markov Model in bisulfite sequencing data.
        DNA methylation studies have enabled researchers to understand
        methylation patterns and their regulatory roles in biological
        processes and disease. However, only a limited number of
        statistical approaches have been developed to provide formal
        quantitative analysis. Specifically, a few available methods do
        identify differentially methylated CpG (DMC) sites or regions
        (DMR), but they suffer from limitations that arise mostly due
        to challenges inherent in bisulfite sequencing data. These
        challenges include: (1) that read-depths vary considerably
        among genomic positions and are often low; (2) both methylation
        and autocorrelation patterns change as regions change; and (3)
        CpG sites are distributed unevenly. Furthermore, there are
        several methodological limitations: almost none of these tools
        is capable of comparing multiple groups and/or working with
        missing values, and only a few allow continuous or multiple
        covariates. The last of these is of great interest among
        researchers, as the goal is often to find which regions of the
        genome are associated with several exposures and traits. To
        tackle these issues, we have developed an efficient DMC
        identification method based on Hidden Markov Models (HMMs)
        called “DMCHMM” which is a three-step approach (model
        selection, prediction, testing) aiming to address the
        aforementioned drawbacks.
Depends: R (>= 4.1.0), SummarizedExperiment, methods, S4Vectors,
        BiocParallel, GenomicRanges, IRanges, fdrtool
Imports: utils, stats, grDevices, rtracklayer, multcomp, calibrate,
        graphics
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
biocViews: DifferentialMethylation, Sequencing, HiddenMarkovModel,
        Coverage
License: GPL-3
Date: 2020-09-27
Encoding: UTF-8
BugReports: https://github.com/shokoohi/DMCHMM/issues
RoxygenNote: 7.1.2
NeedsCompilation: no
Packaged: 2026-01-09 21:14:30 UTC; root
Config/pak/sysreqs: make libbz2-dev liblzma-dev libxml2-dev libssl-dev
        xz-utils zlib1g-dev
Repository: https://bioc.r-universe.dev
Date/Publication: 2025-10-29 14:40:26 UTC
RemoteUrl: https://github.com/bioc/DMCHMM
RemoteRef: HEAD
RemoteSha: 338f80e5dd132b3bc5708b2a789057e7456f0ceb
Built: R 4.6.0; ; 2026-01-09 21:18:19 UTC; windows
