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: 2026-10-26 11:28:07 UTC; root
Author: Xiyu Peng [aut, cre] (ORCID:
        <https://orcid.org/0000-0003-4232-0910>), Nikki Xiao [aut]
Maintainer: Xiyu Peng <pansypeng124@gmail.com>
Repository: https://cran.r-universe.dev
Date/Publication: 2026-05-29 15:00:02 UTC
RemoteUrl: https://github.com/cran/SpaTopic
RemoteRef: HEAD
RemoteSha: f7e1081eb1f9eb9550ca1e72d1dbe90de0af8486