SpaTopic: Topic Inference to Identify Tissue Architecture in Multiplexed
Images
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.
| Version: |
1.3.1 |
| 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 |
| Published: |
2026-05-29 |
| DOI: |
10.32614/CRAN.package.SpaTopic |
| Author: |
Xiyu Peng  [aut,
cre],
Nikki Xiao [aut] |
| Maintainer: |
Xiyu Peng <pansypeng124 at gmail.com> |
| BugReports: |
https://github.com/xiyupeng/SpaTopic/issues |
| License: |
GPL (≥ 3) |
| URL: |
https://xiyupeng.github.io/SpaTopic/,
https://github.com/xiyupeng/SpaTopic,
https://doi.org/10.1038/s41467-025-61821-y |
| NeedsCompilation: |
yes |
| Language: |
en-US |
| Citation: |
SpaTopic citation info |
| Materials: |
README, NEWS |
| CRAN checks: |
SpaTopic results |
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=SpaTopic
to link to this page.