DESCRIPTION

Package: BayesSpace
Version: 1.15.3
Date: 2024-10-21
Title: Clustering and Resolution Enhancement of Spatial Transcriptomes
Authors@R: c(
    person("Edward", "Zhao", role=c("aut"), email="edward130603@gmail.com"),
    person("Senbai", "Kang", role=c("aut"), email="senbai.kang@chuv.ch"),	
    person("Matt", "Stone", role=c("aut", "cre"), email="mstone@fredhutch.org"),
    person("Xing", "Ren", role=c("ctb"), email="xren2@fredhutch.org"),
    person("Raphael", "Gottardo", role=c("ctb"), email="rgottard@fredhutch.org"))
Description: Tools for clustering and enhancing the resolution of spatial gene
    expression experiments. BayesSpace clusters a low-dimensional representation
    of the gene expression matrix, incorporating a spatial prior to encourage
    neighboring spots to cluster together. The method can enhance the resolution
    of the low-dimensional representation into "sub-spots", for which features
    such as gene expression or cell type composition can be imputed.
Depends:
    R (>= 4.0.0),
    SingleCellExperiment
Imports:
    Rcpp (>= 1.0.4.6),
    stats,
    methods,
    purrr,
    scater,
    scran,
    SummarizedExperiment,
    coda,
    rhdf5,
    S4Vectors,
    Matrix,
    magrittr,
    assertthat,
    arrow,
    mclust,
    RCurl,
    DirichletReg,
    xgboost,
    utils,
    dplyr,
    rlang,
    ggplot2,
    tibble,
	  rjson,
    tidyr,
    scales,
	  microbenchmark,
    BiocFileCache,
    BiocSingular,
    BiocParallel
License: MIT + file LICENSE
RoxygenNote: 7.3.2
LinkingTo: 
    Rcpp,
    RcppArmadillo,
    RcppDist,
    RcppProgress
NeedsCompilation: yes
SystemRequirements: C++17
Encoding: UTF-8
Suggests: 
    testthat,
    knitr,
    rmarkdown,
    igraph,
    spatialLIBD,
    viridis,
    patchwork,
    RColorBrewer,
    Seurat
VignetteBuilder: knitr
biocViews:
    Software,
    Clustering,
    Transcriptomics,
    GeneExpression,
    SingleCell,
    ImmunoOncology,
    DataImport
BugReports: https://github.com/edward130603/BayesSpace/issues
URL: edward130603.github.io/BayesSpace