Package: scSpatialSIM
Title: A Point Pattern Simulator for Spatial Cellular Data
Version: 0.1.4
Authors@R: 
    c(
      person(given = "Alex",
             family =  "Soupir", 
             email = "alex.soupir@moffitt.org", 
             role = c("aut"),  
             comment = c(ORCID = "")),
      person(given = "Christopher",
             family =  "Wilson", 
             email = "", 
             role = c("aut"),  
             comment = c(ORCID = "")),
      person(given = "Jordan",
             family = "Creed",
             email = "jordan.creed@moffitt.org",
             role = c("aut"),
             comment = c(ORCID = "")),
      person(given = "Julia", 
             family = "Wrobel", 
             email = "julia.wrobel@cuanschutz.edu", 
             role = c("aut"), 
             comment = c(ORCID = "")),
      person(given = "Oscar", 
             family = "Ospina", 
             email = "oscar.ospina@moffitt.org", 
             role = c("aut"), 
             comment = c(ORCID = "")),
      person(given = "Brooke", 
             family = "Fridley", 
             email = "blfridley@cmh.edu", 
             role = c("aut", "cph"), 
             comment = c(ORCID = "")),
      person(given = "Fridley",
             family = "Lab", 
             email = "fridley.lab@moffitt.org",
             role = c("cre"))
    )
Description: Single cell resolution data has been valuable in learning
        about tissue microenvironments and interactions between cells
        or spots. This package allows for the simulation of this level
        of data, be it single cell or ‘spots’, in both a univariate
        (single metric or cell type) and bivariate (2 or more metrics
        or cell types) ways. As more technologies come to marker, more
        methods will be developed to derive spatial metrics from the
        data which will require a way to benchmark methods against each
        other. Additionally, as the field currently stands, there is
        not a gold standard method to be compared against. We set out
        to develop an R package that will allow users to simulate point
        patterns that can be biologically informed from different
        tissue domains, holes, and varying degrees of
        clustering/colocalization. The data can be exported as spatial
        files and a summary file (like 'HALO').
        <https://github.com/FridleyLab/scSpatialSIM/>.
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.2.3
Imports: dplyr, ggplot2, magrittr, spatstat.geom, crayon, ggpubr,
        pbmcapply, spatstat.random, tidyr, utils, methods, proxy
Depends: R (>= 4.00)
LazyData: true
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), spatialTIME, spdep
VignetteBuilder: knitr
License: MIT + file LICENSE
Config/testthat/edition: 3
URL: https://github.com/FridleyLab/scSpatialSIM
Config/pak/sysreqs: cmake make libicu-dev
Repository: https://fridleylab.r-universe.dev
Date/Publication: 2026-02-16 17:32:58 UTC
RemoteUrl: https://github.com/fridleylab/scspatialsim
RemoteRef: HEAD
RemoteSha: 663d7ae1ae6309c9464421c981e2d94709a4530f
NeedsCompilation: no
Packaged: 2026-06-16 08:36:00 UTC; root
Author: Alex Soupir [aut],
  Christopher Wilson [aut],
  Jordan Creed [aut],
  Julia Wrobel [aut],
  Oscar Ospina [aut],
  Brooke Fridley [aut, cph],
  Fridley Lab [cre]
Maintainer: Fridley Lab <fridley.lab@moffitt.org>