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SpaTopic

1.3.1

Topic Inference to Identify Tissue Architecture in Multiplexed Images

0packages depend
2.6Kdownloads / year
0.0%test coverage
13/13checks pass

Overview

About
Maintained by Xiyu PengFirst published 2024-01-174 releasesCRAN page ↗GitHub ↗

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.

Install

Health

CRAN checks
13OK
Slowest check: 5.9 min · r-release-macos-x86_64
Code health
Yes
Tests · ratio 0.00
0.0%
Coverage · measured lines
100%
Documentation · exports
6
Dependencies · direct
Check history
  • OK2026-08-05
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • NOTE2026-08-01
    12 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • OK2026-05-01
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • ERROR2026-04-28
    12 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
  • OK2026-04-22
    14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Show 4 earlier snapshots
  • ERROR2026-04-18
    13 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
  • OK2026-04-10
    14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • ERROR2026-04-09
    13 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
  • OK2026-03-10
    14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
READMEYes · 516 wordsVignettesYes · dynamicpkgdown siteNoNEWSYes · 100% structuredCode of conductNoContributing guideNo
Examples that run
83%
Documented parameters
100%
Return-value docs
100%
References docs
0%

Downloads

2.6K
CRAN downloads in the past year
Rank #9,571 · ~7/day · ~215/mo
Daily download trend is not available in this view yet.
19630 days
98690 days
2.6K1 year
Compare downloads with other packages →
Also on401 r2u19 autocran

Repository

Repository
18Stars
3Forks
0Open issues
0Open PRs
4Releases
129Commits
3Contributors
License GPL-3.0 · 129 commits · Last activity 2026-06-05 · 0% stars, 30d

Stars over time

2025-07-18 · 102026-07-07 · 18

Repository practices

Upstream repositoryBeta

2 development-tooling and community-health practices detected across 2 families in the upstream repository

Checks run against github.com/xiyupeng/spatopic on 2026-08-16.

Continuous integration (1)
GitHub Actions
CRAN release process (1)
cran-comments.md
How this is detected·Detection ruleset v1 (2026-07-18)

Dependencies

Declared dependencies
14 external dependencies (excludes base and recommended)
Depends (1)
R >= 3.5.0
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Code & Tests

Datasets

People & History

People (2)
Maintainer (1)
Author, Maintainer
Authors (2)
Author, Maintainer
Author · added in 1.3.1
Package Timeline

4 releases. Pick two to compare their code metrics. R releases are shown for context.

  • 1.3.1Latest
    2026-05-29 · current release · diff ↗
  • R
    R 4.6.0 released · 2026-04-24
  • R
    R 4.5.0 released · 2025-04-11
  • 1.2.0
    2025-03-03 · diff ↗
  • R
    R 4.4.0 released · 2024-04-24
  • 1.1.0
    2024-04-23 · diff ↗
  • 1.0.1
    2024-01-17
  • R
    R 4.3.0 released · 2023-04-21

Package metadata

First published
2024-01-17
Total releases
4 / 2 yrs
License
GPL (>= 3) OSI
Minimum R
≥ 3.5.0
Bundled data
487 KB / 1 file
Download size
433 KB
Installed size
not tracked yet
With dependencies
not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("SpaTopic")
Peng, X., & Xiao, N. (2026). SpaTopic: Topic Inference to Identify Tissue Architecture in Multiplexed Images (Version 1.3.1) [Computer software]. https://doi.org/10.32614/CRAN.package.SpaTopic

This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for SpaTopic version 1.3.1 [Data set]. HJJB, LLC. Data release v2026-08-16. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-16, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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