DESCRIPTION

Package: scFeatures
Title: scFeatures: Multi-view representations of single-cell and spatial data
       for disease outcome prediction
Version: 1.3.4
Authors@R: 
    c(
    person(given = "Yue",family = "Cao", email = "yue.cao@sydney.edu.au",  role=c("aut", "cre")),
    person(given = "Yingxin",family = "Lin", email = "yingxin.lin@sydney.edu.au",  role="aut" ),
    person(given = "Ellis",family = "Patrick", email = "ellis.patrick@sydney.edu.au",  role="aut" ),
    person(given = "Pengyi",family = "Yang", email = "pengyi.yang@sydney.edu.au",  role="aut" ),
    person(given = "Jean Yee Hwa",family = "Yang", email = "jean.yang@sydney.edu.au",  role="aut" ))
Description: scFeatures constructs multi-view representations of single-cell
             and spatial data. scFeatures is a tool that generates multi-view
             representations of single-cell and spatial data through the
             construction of a total of 17 feature types. These features can 
             then be used for a variety of analyses using other software in
             Biocondutor.
License: GPL-3
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.2.3
biocViews: CellBasedAssays, SingleCell, Spatial, Software, Transcriptomics
Depends: R (>= 4.2.0)
Imports:
    DelayedArray,
    DelayedMatrixStats,
    EnsDb.Hsapiens.v79,
    EnsDb.Mmusculus.v79,
    GSVA,
    ape,
    glue,
    dplyr,
    ensembldb,
    gtools,
    msigdbr,
    proxyC,
    reshape2,
    spatstat.explore,
    spatstat.geom,
    tidyr,
    AUCell,
    BiocParallel,
    rmarkdown,
    methods,
    stats,
    cli,
    SingleCellSignalR,
    MatrixGenerics,
    Seurat,
    DT
Suggests: 
    knitr,
    S4Vectors,
    survival,
    survminer,
    BiocStyle,
    ClassifyR,
    org.Hs.eg.db,
    clusterProfiler
VignetteBuilder: knitr
URL: https://sydneybiox.github.io/scFeatures/ https://github.com/SydneyBioX/scFeatures/
BugReports: https://github.com/SydneyBioX/scFeatures/issues