DESCRIPTION

Package: nnSVG
Version: 1.5.4
Title: Scalable identification of spatially variable genes in 
    spatially-resolved transcriptomics data
Description: Method for scalable identification of spatially variable genes 
    (SVGs) in spatially-resolved transcriptomics data. The method is based on 
    nearest-neighbor Gaussian processes and uses the BRISC algorithm for model 
    fitting and parameter estimation. Allows identification and ranking of SVGs 
    with flexible length scales across a tissue slide or within spatial domains 
    defined by covariates. Scales linearly with the number of spatial locations 
    and can be applied to datasets containing thousands or more spatial 
    locations.
Authors@R: c(
    person("Lukas M.", "Weber", 
           email = "lukas.weber.edu@gmail.com", 
           role = c("aut", "cre"), 
           comment = c(ORCID = "0000-0002-3282-1730")), 
    person("Stephanie C.", "Hicks", 
           email = "shicks19@jhu.edu", 
           role = c("aut"), 
           comment = c(ORCID = "0000-0002-7858-0231")))
URL: https://github.com/lmweber/nnSVG
BugReports: https://github.com/lmweber/nnSVG/issues
License: MIT + file LICENSE
Encoding: UTF-8
biocViews: 
    Spatial, 
    SingleCell, 
    Transcriptomics, 
    GeneExpression, 
    Preprocessing
Depends: 
    R (>= 4.0)
Imports: 
    SpatialExperiment, 
    SingleCellExperiment, 
    SummarizedExperiment, 
    BRISC, 
    BiocParallel, 
    Matrix, 
    matrixStats, 
    stats, 
    methods
VignetteBuilder: knitr
Suggests: 
    BiocStyle, 
    knitr, 
    rmarkdown, 
    STexampleData, 
    WeberDivechaLCdata, 
    scran, 
    ggplot2, 
    testthat
RoxygenNote: 7.2.3