DESCRIPTION

Package: sccomp
Title: Robust Outlier-aware Estimation of Composition and Heterogeneity for Single-cell Data
Version: 2.1.0
Authors@R: c(person("Stefano", "Mangiola", email = "mangiolastefano@gmail.com",
                  role = c("aut", "cre"))
                  )
Description: A robust and outlier-aware method for testing differential tissue composition from single-cell data. This model can infer changes in tissue composition and heterogeneity, and can produce realistic data simulations based on any existing dataset. This model can also transfer knowledge from a large set of integrated datasets to increase accuracy further.
License: GPL-3 
URL: https://github.com/MangiolaLaboratory/sccomp
BugReports: https://github.com/MangiolaLaboratory/sccomp/issues
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.3
Depends: R (>= 4.2.0)
Imports:
    instantiate (>= 0.2.3),
    stats,
    SingleCellExperiment,
    parallel,
    dplyr,
    tidyr,
    purrr,
    magrittr,
    rlang,
    tibble,
    boot,
    lifecycle,
    tidyselect,
    utils,
    ggplot2,
    ggrepel,
    patchwork,
    forcats,
    readr,
    scales,
    stringr,
    glue
Suggests:
    knitr,
    rmarkdown,
    BiocStyle,
    testthat (>= 3.0.0),
    markdown,
    loo,
    prettydoc,
    tidyseurat,
    tidySingleCellExperiment,
    bayesplot,
    posterior
Additional_repositories:
    https://mc-stan.org/r-packages/
SystemRequirements: CmdStan (https://mc-stan.org/users/interfaces/cmdstan)
biocViews: Bayesian, Regression, DifferentialExpression, SingleCell
LazyData: true
VignetteBuilder: knitr