CARDspa
Bioc currentSpatially Informed Cell Type Deconvolution for Spatial Transcriptomics
Release Lineage
Entered 3.21 · Apr 16, 2025
Current · Requires R 4.6
Description
CARD is a reference-based deconvolution method that estimates cell type composition in spatial transcriptomics based on cell type specific expression information obtained from a reference scRNA-seq data. A key feature of CARD is its ability to accommodate spatial correlation in the cell type composition across tissue locations, enabling accurate and spatially informed cell type deconvolution as well as refined spatial map construction. CARD relies on an efficient optimization algorithm for constrained maximum likelihood estimation and is scalable to spatial transcriptomics with tens of thousands of spatial locations and tens of thousands of genes.
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
29 9 exported
Complexity
6.2 avg / 26 max
Call network
29 nodes / 18 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
4,997
Files
69
Compiled share
8.3%
Has compiled src
Yes
Language breakdown
API
Exported functions
9
Internal functions
15
Recent export changes
Testing & CI
Has tests
Yes
Test-to-code ratio
0.05
testthat edition
–
CI present
No
CI type
[]
PR gated
No
Docs
Roxygen coverage
100%
Health & Security signals
Informational signals; not verdicts.
on.exit coverage
0%
Unsafe pattern score
0
Dep constraint coverage
3.6%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
4.3.0
System requirements
–
C++ standard
–
License
GPL-3 + file LICENSE
License flags
SPDX valid, OSI approved
History
Versions
3
First release
2025-04-15
Latest release
2026-04-28
Avg cadence
189 days
Cold removal rate
–
Dep drift
1
LOC over versions
Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.
Documentation
- Examples that run
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 0%
Topics
Depended on by (1)
Bioconductor (1)
People
Cite
Cite this package
Run in R for the authors' preferred citation:
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Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
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