Package: SPIAT
Type: Package
Title: Spatial Image Analysis of Tissues
Version: 1.0.4
Authors@R: c(
    person(given = "Anna",
           family="Trigos",
           role=c("aut"),
           email="anna.trigos@petermac.org"),
    person(given = "Yuzhou",
           family = " Feng",
           role=c("aut", "cre"),
           email="yuzhou.feng@petermac.org"),
    person(given = "Tianpei",
           family = " Yang",
           role="aut",
           email="yangtp3344@gmail.com"),
    person(given = "Mabel",
           family = " Li",
           role="aut"),
    person(given = "John",
           family = " Zhu",
           role="aut"),
    person(given = "Volkan",
           family=" Ozcoban",
           role="aut",
           email = "volkanozcoban1@gmail.com"),
    person(given = "Maria",
           family= "Doyle",
           role="aut",
           email = "maria.doyle@petermac.org"))
Description: SPIAT (**Sp**atial **I**mage **A**nalysis of **T**issues) is an R 
    package with a suite of data processing, quality control, visualization and data 
    analysis tools. SPIAT is compatible with data generated from single-cell spatial 
    proteomics platforms (e.g. OPAL, CODEX, MIBI, cellprofiler). SPIAT reads spatial 
    data in the form of X and Y coordinates of cells, marker intensities and cell 
    phenotypes. SPIAT includes six analysis modules that allow visualization, 
    calculation of cell colocalization, categorization of the immune 
    microenvironment relative to tumor areas, analysis of cellular neighborhoods, 
    and the quantification of spatial heterogeneity, providing a comprehensive 
    toolkit for spatial data analysis.
License: Artistic-2.0
Encoding: UTF-8
Depends: R (>= 4.2.0), SpatialExperiment
Imports: apcluster (>= 1.4.7), ggplot2 (>= 3.2.1), gridExtra (>= 2.3),
        gtools (>= 3.8.1), reshape2 (>= 1.4.3), dplyr (>= 0.8.3),
        plotly (>= 4.9.0), RANN (>= 2.6.1), pracma (>= 2.2.5), dbscan
        (>= 1.1-5), mmand (>= 1.5.4), tibble (>= 2.1.3), grDevices,
        stats, utils, vroom, ComplexHeatmap, dittoSeq, spatstat.geom,
        alphahull, methods, spatstat.explore, raster, sp, elsa, Rtsne,
        umap, rlang, graphics, SummarizedExperiment
Suggests: BiocStyle, knitr, rmarkdown, pkgdown, testthat, xROI
biocViews: BiomedicalInformatics, CellBiology, Spatial, Clustering,
        DataImport, ImmunoOncology, QualityControl, SingleCell,
        Software, Visualization
BugReports: https://github.com/trigosteam/SPIAT/issues
RoxygenNote: 7.2.0
LazyData: true
VignetteBuilder: knitr
URL: https://trigosteam.github.io/SPIAT/
git_url: https://git.bioconductor.org/packages/SPIAT
git_branch: RELEASE_3_16
git_last_commit: cff761f
git_last_commit_date: 2022-12-19
Date/Publication: 2022-12-20
NeedsCompilation: no
Packaged: 2022-12-21 02:56:08 UTC; biocbuild
Author: Anna Trigos [aut],
  Yuzhou Feng [aut, cre],
  Tianpei Yang [aut],
  Mabel Li [aut],
  John Zhu [aut],
  Volkan Ozcoban [aut],
  Maria Doyle [aut]
Maintainer: Yuzhou  Feng <yuzhou.feng@petermac.org>
Built: R 4.2.2; ; 2022-12-21 12:22:06 UTC; windows
