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scDataviz

Bioc current

scDataviz: single cell dataviz and downstream analyses

v1.22.0 · software · GPL-3

Release Lineage

Entered 3.12 · Oct 28, 2020

Current · Requires R 4.6

1.0 In 12 of 49 releases 3.23

Description

In the single cell World, which includes flow cytometry, mass cytometry, single-cell RNA-seq (scRNA-seq), and others, there is a need to improve data visualisation and to bring analysis capabilities to researchers even from non-technical backgrounds. scDataviz attempts to fit into this space, while also catering for advanced users. Additonally, due to the way that scDataviz is designed, which is based on SingleCellExperiment, it has a 'plug and play' feel, and immediately lends itself as flexibile and compatibile with studies that go beyond scDataviz. Finally, the graphics in scDataviz are generated via the ggplot engine, which means that users can 'add on' features to these with ease.

Test coverage

Line coverage

Expression

Tests / Examples

Functions

13 13 exported

Complexity

14.6 avg / 29 max

Call network

13 nodes / 6 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

4,804

Files

52

Compiled share

0%

Has compiled src

No

Language breakdown

R 2,485 (51.7%)Tests 1 (0%)Docs 1,582 (32.9%)Vignettes 736 (15.3%)

API

Exported functions

13

Internal functions

0

Testing & CI

Has tests

Yes

Test-to-code ratio

0.00

testthat edition

CI present

No

CI type

[]

PR gated

No

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

4.0

System requirements

C++ standard

License

GPL-3

License flags

SPDX valid, OSI approved

History

Versions

12

First release

2020-10-27

Latest release

2026-04-28

Avg cadence

182 days

Cold removal rate

Dep drift

0

LOC over versions

v3.12: 4,788 LOCv3.13: 4,795 LOCv3.14: 4,804 LOCv3.15: 4,804 LOCv3.16: 4,804 LOCv3.17: 4,804 LOCv3.18: 4,804 LOCv3.19: 4,804 LOCv3.20: 4,804 LOCv3.21: 4,804 LOCv3.22: 4,804 LOCv3.23: 4,804 LOC

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

Documentation

Documentation
READMEYes · 3,160 wordsVignettesYes · dynamicpkgdown siteNoNEWSNoCode of conductNoContributing guideNo
Examples that run
100%
Documented parameters
91%
Return-value docs
100%
References docs
0%

Topics

People

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("scDataviz")
Blighe, K. (2026). scDataviz: scDataviz: single cell dataviz and downstream analyses (Version 1.22.0) [Computer software]. https://bioconductor.org/packages/scDataviz

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 scDataviz version 1.22.0 [Data set]. HJJB, LLC. Data release v2026-08-25. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-25, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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