Package: sccomp
Title: Robust Outlier-aware Estimation of Composition and Heterogeneity for Single-cell Data
Version: 1.7.0
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 
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.2.3
Biarch: true
Depends: 
    R (>= 4.2.0)
Imports: 
    methods,
    Rcpp (>= 0.12.0),
    RcppParallel (>= 5.0.1),
    rstantools (>= 2.1.1),
    rstan (>= 2.26.0),
    SeuratObject,
    SingleCellExperiment,
    parallel,
    dplyr,
    tidyr,
    purrr,
    magrittr,
    rlang,
    tibble,
    boot,
    lifecycle,
    stats,
    tidyselect,
    utils,
    ggplot2,
    ggrepel,
    patchwork,
    forcats,
    readr,
    scales,
    stringr,
    glue
Suggests:
    BiocStyle,
    testthat (>= 3.0.0),
    markdown,
    knitr,
    tidyseurat,
    tidySingleCellExperiment,
    loo
Enhances:
    furrr,
    extraDistr
LinkingTo: 
    BH (>= 1.66.0),
    Rcpp (>= 0.12.0),
    RcppEigen (>= 0.3.3.3.0),
    RcppParallel (>= 5.0.1),
    rstan (>= 2.26.0),
    StanHeaders (>= 2.26.0)
SystemRequirements: GNU make
VignetteBuilder: 
    knitr
RdMacros:
    lifecycle
biocViews: 
    ImmunoOncology, 
    Normalization, 
    Sequencing, 
    RNASeq, 
    Software, 
    GeneExpression,
    Transcriptomics, 
    SingleCell, 
    Clustering
LazyDataCompression: xz
Config/testthat/edition: 3
URL: https://github.com/stemangiola/sccomp
BugReports: https://github.com/stemangiola/sccomp/issues
Additional_repositories:
    https://mc-stan.org/r-packages/