BayesSpace
Bioc currentClustering and Resolution Enhancement of Spatial Transcriptomes
Release Lineage
Entered 3.12 · Oct 28, 2020
Current · Requires R 4.6
Description
Tools for clustering and enhancing the resolution of spatial gene expression experiments. BayesSpace clusters a low-dimensional representation of the gene expression matrix, incorporating a spatial prior to encourage neighboring spots to cluster together. The method can enhance the resolution of the low-dimensional representation into "sub-spots", for which features such as gene expression or cell type composition can be imputed.
None published for Bioconductor
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
94 18 exported
Complexity
3.9 avg / 20 max
Call network
94 nodes / 75 edges
Test coverage is not measured for Bioconductor packages; nodes fall back to a neutral fill.
Call graph
Open call graph →Lowest coverage
Per-function coverage is not measured for this package yet.
Code
Structure
Lines of code
6,801
Files
88
Compiled share
26.5%
Has compiled src
Yes
Language breakdown
API
Exported functions
18
Internal functions
45
Recent export changes
Testing
Has tests
Yes
Test-to-code ratio
0.08
testthat edition
–
Docs
Roxygen coverage
100%
Health & Security signals
Informational signals; not verdicts.
on.exit coverage
0%
Unsafe pattern score
0
Dep constraint coverage
6.5%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
4.0.0
System requirements
1 externalC++17
C++ standard
C++17
License
MIT + file LICENSE
License flags
SPDX valid, OSI approved
History
Versions
12
First release
2020-10-27
Latest release
2026-04-28
Avg cadence
177 days
Cold removal rate
–
Dep drift
11
LOC over versions
Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.
Documentation
- Help pages
- 42 (30 internal)includes a package overview page
- Examples that run
- 91%10 run in a plain check · 1 never run
- Exported functions with examples
- 92%
- Documented parameters
- 94%
- Return-value docs
- 100%
- Help pages citing references
- 0%
- BayesSpace HTML
Repository practices
1 development-tooling and community-health practice detected across 1 family in the upstream repository
Checks run against github.com/edward130603/bayesspace on 2026-10-22.
GitHub Pages site last deployed 2021-08-04
Datasets
| Name | Class | Size | Also in |
|---|---|---|---|
| 151673.Giotto_HMRF | data.frame | 3,639 × 3 | No other package |
| 151673.stLearn_HVGs | data.frame | 3,639 × 3 | No other package |
| 151673.stLearn_markers | data.frame | 3,639 × 3 | No other package |
| ST_mel1_rep2 | – | – | – |
| ST_mel1_rep2.Giotto_HMRF | data.frame | 293 × 2 | No other package |
Topics
Depended on by (2)
Bioconductor (2)
People
- Senbai Kang author maintainer
- Raphael Gottardo contributor
- Xing Ren contributor
- Matt Stone author
- Edward Zhao author
Cite
Cite this package
Run in R for the authors' entry:
citation("BayesSpace")The package provides a citation file, so citation() returns the authors' own entry.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-23, which the citation names so these numbers can be found later. More on citing and the projects behind them.