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tpSVG

Bioc current

Thin plate models to detect spatially variable genes

v1.8.0 · Package record · software · MIT + file LICENSE

Release Lineage

Entered 3.19 · May 1, 2024

Current · Requires R 4.6

1.0 In 5 of 49 releases 3.23

Description

The goal of `tpSVG` is to detect and visualize spatial variation in the gene expression for spatially resolved transcriptomics data analysis. Specifically, `tpSVG` introduces a family of count-based models, with generalizable parametric assumptions such as Poisson distribution or negative binomial distribution. In addition, comparing to currently available count-based model for spatially resolved data analysis, the `tpSVG` models improves computational time, and hence greatly improves the applicability of count-based models in SRT data analysis.

Advisories

None published for Bioconductor

Test coverage

Line coverage

–

Expression

–

Tests / Examples

–

Functions

1 1 exported

Complexity

18 avg / 18 max

Call network

1 nodes / 0 edges

Test coverage is not measured for Bioconductor packages; nodes fall back to a neutral fill.

Loading call graph…

Lowest coverage

Per-function coverage is not measured for this package yet.

Code

Structure

Lines of code

674

Files

12

Compiled share

0%

Has compiled src

No

Language breakdown

R 273 (40.5%)Tests 39 (5.8%)Docs 150 (22.3%)Vignettes 212 (31.5%)

API

Exported functions

1

Internal functions

0

Recent export changes

v3.19+1 tpSVG

Testing

Has tests

Yes

Test-to-code ratio

0.14

testthat edition

3

Docs

Roxygen coverage

100%

Health & Security signals

Informational signals; not verdicts.

on.exit coverage

–

Unsafe pattern score

0

Dep constraint coverage

0%

Secret pattern count

0

Bundled 3rd-party code

2 items

Portability & License

Min R version

4.4

System requirements

–

C++ standard

–

License

MIT + file LICENSE

License flags

SPDX valid, OSI approved

History

Versions

5

First release

2024-04-30

Latest release

2026-04-28

Avg cadence

182 days

Cold removal rate

–

Dep drift

0

LOC over versions

v3.19: 674 LOCv3.20: 674 LOCv3.21: 674 LOCv3.22: 674 LOCv3.23: 674 LOC

Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.

Documentation

In the Bioconductor 3.23 release
READMEYes · 467 wordsVignettesYes · 1 · dynamicNEWSYes · 100% structuredCitation fileNo
Help pages
1
Examples that run
100%1 run in a plain check
Exported functions with examples
100%
Documented parameters
91%
Return-value docs
100%
Help pages citing references
0%
Vignettes (1)

Repository practices

Upstream repositoryBeta

8 development-tooling and community-health practices detected across 4 families in the upstream repository

Checks run against github.com/boyiguo1/tpsvg on 2026-10-22.

Continuous integration (2)
GitHub ActionsR CMD check workflow

The R CMD check workflow runs on Linux, macOS and Windows, and on R-devel

Governance and community (1)
Issue templates
Docs source (4)
README.Rmdpkgdown

GitHub Pages site last deployed 2024-02-28 · The repository has a site deploy workflow

Coverage (1)
Coverage reporting
How this is detected·Detection ruleset v4 (2026-10-20)

Topics

Maintainer
Boyi Guo

Available on

CRANr2uBioconductorautoCRANCOPR

People

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("tpSVG")
Guo, B., Hicks, S. C., & Weber, L. M. (2026). tpSVG: Thin plate models to detect spatially variable genes (Version 1.8.0) [Computer software]. https://bioconductor.org/packages/tpSVG

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

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 tpSVG version 1.8.0 [Data set]. HJJB, LLC. Data release v2026-10-25. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-25, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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