Package: SpaTopic
Type: Package
Title: Topic Inference to Identify Tissue Architecture in Multiplexed
        Images
Version: 1.3.1
Date: 2026-05-27
Authors@R: c(
  person("Xiyu", "Peng", email = "pansypeng124@gmail.com",
    role = c("aut", "cre"),comment = c(ORCID = "0000-0003-4232-0910")),
  person("Nikki", "Xiao", email = "xmq041117@gmail.com",
    role = c("aut"))
  )
Description: A novel spatial topic model to integrate both cell type and spatial information to identify the complex spatial tissue architecture on multiplexed tissue images without human intervention. The Package implements a collapsed Gibbs sampling algorithm for inference. The method is highly scalable to large-scale image datasets without extracting neighborhood information for every single cell. The package supports spatially resolved cell-level data analysis, topic inference, visualization, and downstream biological interpretation of tissue microenvironments.
License: GPL (>= 3)
Depends: R (>= 3.5.0),
Imports: Rcpp (>= 0.12.0), RANN (>= 2.6.0), sf (>= 1.0-12), methods (>=
        3.4), foreach (>= 1.5.0), iterators (>= 1.0),
LinkingTo: Rcpp, RcppArmadillo, RcppProgress,
Suggests: knitr, rmarkdown, SeuratObject (>= 4.9.9.9086), doParallel
        (>= 1.0), spelling
VignetteBuilder: knitr
RoxygenNote: 7.3.2
Encoding: UTF-8
LazyData: true
URL: https://xiyupeng.github.io/SpaTopic/,
        https://github.com/xiyupeng/SpaTopic,
        https://doi.org/10.1038/s41467-025-61821-y
BugReports: https://github.com/xiyupeng/SpaTopic/issues
Language: en-US
NeedsCompilation: yes
Packaged: 2026-05-27 21:43:57 UTC; xiyupeng
Author: Xiyu Peng [aut, cre] (ORCID: <https://orcid.org/0000-0003-4232-0910>),
  Nikki Xiao [aut]
Maintainer: Xiyu Peng <pansypeng124@gmail.com>
Repository: CRAN
Date/Publication: 2026-05-29 15:00:02 UTC
Built: R 4.6.0; x86_64-w64-mingw32; 2026-06-09 03:02:25 UTC; windows
Archs: x64
