Package: BASiCS
Type: Package
Title: Bayesian Analysis of Single-Cell Sequencing data
Version: 2.23.0
Date: 2025-09-17
Authors@R: c(person("Catalina", "Vallejos", role=c("aut", "cre"),
        email="catalina.vallejos@igmm.ed.ac.uk",
        comment=c(ORCID = "0000-0003-3638-1960")), 
        person("Nils", "Eling", role=c("aut")), 
        person("Alan", "O'Callaghan", role = c("aut")),
        person("Sylvia", "Richardson", role = c("ctb")), 
        person("John", "Marioni", role=c("ctb"))) 
Description: Single-cell mRNA sequencing can uncover novel cell-to-cell
        heterogeneity in gene expression levels in seemingly
        homogeneous populations of cells. However, these experiments
        are prone to high levels of technical noise, creating new
        challenges for identifying genes that show genuine
        heterogeneous expression within the population of cells under
        study. BASiCS (Bayesian Analysis of Single-Cell Sequencing
        data) is an integrated Bayesian hierarchical model to perform
        statistical analyses of single-cell RNA sequencing datasets in
        the context of supervised experiments (where the groups of
        cells of interest are known a priori, e.g. experimental
        conditions or cell types). BASiCS performs built-in data
        normalisation (global scaling) and technical noise
        quantification (based on spike-in genes). BASiCS provides an
        intuitive detection criterion for highly (or lowly) variable
        genes within a single group of cells. Additionally, BASiCS can
        compare gene expression patterns between two or more
        pre-specified groups of cells. Unlike traditional differential
        expression tools, BASiCS quantifies changes in expression that
        lie beyond comparisons of means, also allowing the study of
        changes in cell-to-cell heterogeneity. The latter can be
        quantified via a biological over-dispersion parameter that
        measures the excess of variability that is observed with
        respect to Poisson sampling noise, after normalisation and
        technical noise removal. Due to the strong mean/over-dispersion
        confounding that is typically observed for scRNA-seq datasets,
        BASiCS also tests for changes in residual over-dispersion,
        defined by residual values with respect to a global
        mean/over-dispersion trend.
License: GPL-3
Depends: R (>= 4.1), SingleCellExperiment
Imports: Biobase, BiocGenerics, coda, cowplot, ggExtra, ggplot2,
        graphics, grDevices, MASS, methods, Rcpp (>= 0.11.3),
        S4Vectors, scran, scuttle, stats, stats4, SummarizedExperiment,
        viridis, utils, Matrix (>= 1.5.0), matrixStats, assertthat,
        reshape2, BiocParallel, posterior, hexbin
Suggests: BiocStyle, knitr, rmarkdown, testthat, scRNAseq, magick
LinkingTo: Rcpp, RcppArmadillo
VignetteBuilder: knitr
biocViews: ImmunoOncology, Normalization, Sequencing, RNASeq, Software,
        GeneExpression, Transcriptomics, SingleCell,
        DifferentialExpression, Bayesian, CellBiology, ImmunoOncology
NeedsCompilation: yes
URL: https://github.com/catavallejos/BASiCS
BugReports: https://github.com/catavallejos/BASiCS/issues
RoxygenNote: 7.3.3
Encoding: UTF-8
LazyData: false
Config/testthat/edition: 3
Collate: 'AllClasses.R' 'AllGenerics.R' 'BASiCS_CalculateERCC.R'
        'BASiCS_CorrectOffset.R' 'BASiCS_DenoisedCounts.R'
        'BASiCS_DenoisedRates.R' 'BASiCS_DetectHVG_LVG.R'
        'BASiCS_DiagHist.R' 'BASiCS_DiagPlot.R'
        'BASiCS_DivideAndConquer.R' 'BASiCS_Draw.R'
        'BASiCS_EffectiveSize.R' 'BASiCS_Filter.R' 'BASiCS_LoadChain.R'
        'BASiCS_MCMC.R' 'BASiCS_MockSCE.R' 'BASiCS_Package.R'
        'BASiCS_PlotDE.R' 'BASiCS_PlotOffset.R' 'BASiCS_PlotVG.R'
        'BASiCS_PlotVarianceDecomp.R' 'BASiCS_PriorParam.R'
        'BASiCS_ShowFit.R' 'BASiCS_Sim.R' 'BASiCS_TestDE.R'
        'BASiCS_VarThresholdSearchHVG_LVG.R' 'BASiCS_VarianceDecomp.R'
        'HiddenBASiCS_Sim.R' 'HiddenHeaderBASiCS_Sim.R'
        'HiddenHeaderTest_DE.R' 'HiddenVarDecomp.R' 'utils_Misc.R'
        'Methods.R' 'RcppExports.R' 'data.R' 'makeExampleBASiCS_Data.R'
        'newBASiCS_Chain.R' 'newBASiCS_Data.R' 'utils_Data.R'
        'utils_DivideAndConquer.R' 'utils_MCMC.R' 'utils_Store.R'
        'utils_Tests.R' 'utils_VG.R' 'welcome.R'
Config/pak/sysreqs: libglpk-dev make libicu-dev libxml2-dev zlib1g-dev
Repository: https://bioc.r-universe.dev
Date/Publication: 2025-10-29 14:41:03 UTC
RemoteUrl: https://github.com/bioc/BASiCS
RemoteRef: HEAD
RemoteSha: c192abaa818a860db7d36d5fc2e6daa9ab34921e
Packaged: 2026-03-10 08:16:54 UTC; root
Author: Catalina Vallejos [aut, cre] (ORCID:
    <https://orcid.org/0000-0003-3638-1960>),
  Nils Eling [aut],
  Alan O'Callaghan [aut],
  Sylvia Richardson [ctb],
  John Marioni [ctb]
Maintainer: Catalina Vallejos <catalina.vallejos@igmm.ed.ac.uk>
Built: R 4.6.0; x86_64-w64-mingw32; 2026-03-10 08:20:15 UTC; windows
Archs: x64
