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celda

Bioc current

CEllular Latent Dirichlet Allocation

v1.28.0 · software · MIT + file LICENSE

Release Lineage

Entered 3.9 · May 3, 2019

Current · Requires R 4.6

1.0 In 15 of 49 releases 3.23

Description

Celda is a suite of Bayesian hierarchical models for clustering single-cell RNA-sequencing (scRNA-seq) data. It is able to perform "bi-clustering" and simultaneously cluster genes into gene modules and cells into cell subpopulations. It also contains DecontX, a novel Bayesian method to computationally estimate and remove RNA contamination in individual cells without empty droplet information. A variety of scRNA-seq data visualization functions is also included.

Test coverage

Line coverage

Expression

Tests / Examples

Functions

284 20 exported

Complexity

4 avg / 44 max

Call network

284 nodes / 371 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

33,532

Files

394

Compiled share

5.1%

Has compiled src

Yes

Language breakdown

R 22,778 (67.9%)C/C++/src 1,709 (5.1%)Tests 1,386 (4.1%)Docs 6,301 (18.8%)Vignettes 1,358 (4%)

API

Exported functions

71

Internal functions

216

Recent export changes

v3.9+60 appendCeldaList, availableModels, bestLogLikelihood +57 more
v3.20+3 findMarkersTree, plotDendro, plotMarkerHeatmap

Testing & CI

Has tests

Yes

Test-to-code ratio

0.06

testthat edition

CI present

Yes

CI type

["github-actions"]

PR gated

Yes

Docs

Roxygen coverage

100%

Health & Security signals

Informational signals; not verdicts.

on.exit coverage

0%

Unsafe pattern score

33

Dep constraint coverage

2.6%

Secret pattern count

0

Bundled 3rd-party code

2 items

Portability & License

Min R version

4.0

System requirements

C++ standard

License

MIT + file LICENSE

License flags

SPDX valid, OSI approved

History

Versions

15

First release

2019-06-03

Latest release

2026-04-28

Avg cadence

190 days

Cold removal rate

100%

Dep drift

31

LOC over versions

v3.9: 19,755 LOCv3.10: 22,669 LOCv3.11: 27,703 LOCv3.12: 31,925 LOCv3.13: 29,142 LOCv3.14: 29,942 LOCv3.15: 30,233 LOCv3.16: 30,245 LOCv3.17: 30,257 LOCv3.18: 30,281 LOCv3.19: 30,281 LOCv3.20: 33,532 LOCv3.21: 33,532 LOCv3.22: 33,532 LOCv3.23: 33,532 LOC

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

Documentation

Documentation
READMEYes · 361 wordsVignettesYes · dynamicpkgdown siteYesNEWSYes · 100% structuredCode of conductNoContributing guideNo
Examples that run
99%
Documented parameters
99%
Return-value docs
98%
References docs
0%

Topics

Depended on by (2)

Bioconductor (2)

People

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("celda")
Campbell, J., Corbett, S., Koga, Y., Wang, Z., & Yang, S. (2026). celda: CEllular Latent Dirichlet Allocation (Version 1.28.0) [Computer software]. https://bioconductor.org/packages/celda

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 celda version 1.28.0 [Data set]. HJJB, LLC. Data release v2026-08-22. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-22, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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