Package: scMET
Type: Package
Title: Bayesian modelling of cell-to-cell DNA methylation heterogeneity
Version: 1.13.0
Authors@R: 
    c(person(given = "Andreas C.",
           family = "Kapourani",
           role = c("aut", "cre"),
           email = "kapouranis.andreas@gmail.com",
           comment = c(ORCID = "0000-0003-2303-1953")),
      person(given = "John",
           family = "Riddell",
           role = c("ctb")))
Description: High-throughput single-cell measurements of DNA methylomes
        can quantify methylation heterogeneity and uncover its role in
        gene regulation. However, technical limitations and sparse
        coverage can preclude this task. scMET is a hierarchical
        Bayesian model which overcomes sparsity, sharing information
        across cells and genomic features to robustly quantify genuine
        biological heterogeneity. scMET can identify highly variable
        features that drive epigenetic heterogeneity, and perform
        differential methylation and variability analyses. We
        illustrate how scMET facilitates the characterization of
        epigenetically distinct cell populations and how it enables the
        formulation of novel hypotheses on the epigenetic regulation of
        gene expression.
License: GPL-3
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.2.0
Biarch: true
BugReports: https://github.com/andreaskapou/scMET/issues
Depends: R (>= 4.2.0)
Imports: methods, Rcpp (>= 1.0.0), RcppParallel (>= 5.0.1), rstan (>=
        2.21.3), rstantools (>= 2.1.0), VGAM, data.table, MASS,
        logitnorm, ggplot2, matrixStats, assertthat, viridis, coda,
        BiocStyle, cowplot, stats, SummarizedExperiment,
        SingleCellExperiment, Matrix, dplyr, S4Vectors
Suggests: testthat, knitr, rmarkdown
LinkingTo: BH (>= 1.66.0), Rcpp (>= 1.0.0), RcppEigen (>= 0.3.3.3.0),
        RcppParallel (>= 5.0.1), rstan (>= 2.21.3), StanHeaders (>=
        2.21.0.7)
SystemRequirements: GNU make
biocViews: ImmunoOncology, DNAMethylation, DifferentialMethylation,
        DifferentialExpression, GeneExpression, GeneRegulation,
        Epigenetics, Genetics, Clustering, FeatureExtraction,
        Regression, Bayesian, Sequencing, Coverage, SingleCell
VignetteBuilder: knitr
Config/pak/sysreqs: make zlib1g-dev
Repository: https://bioc.r-universe.dev
Date/Publication: 2025-10-29 15:17:57 UTC
RemoteUrl: https://github.com/bioc/scMET
RemoteRef: HEAD
RemoteSha: 5af0e5e683aeb6b91879351b2ed1c9fef0494ab8
NeedsCompilation: yes
Packaged: 2025-10-30 10:32:09 UTC; root
Author: Andreas C. Kapourani [aut, cre] (ORCID:
    <https://orcid.org/0000-0003-2303-1953>),
  John Riddell [ctb]
Maintainer: Andreas C. Kapourani <kapouranis.andreas@gmail.com>
Built: R 4.6.0; x86_64-w64-mingw32; 2025-10-30 10:35:15 UTC; windows
Archs: x64
