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APL

Bioc current

Association Plots

v1.16.0 · Package record · software · GPL (>= 3)

Release Lineage

Entered 3.15 · Apr 27, 2022

Current · Requires R 4.6

1.0 In 9 of 49 releases 3.23

Description

APL is a package developed for computation of Association Plots (AP), a method for visualization and analysis of single cell transcriptomics data. The main focus of APL is the identification of genes characteristic for individual clusters of cells from input data. The package performs correspondence analysis (CA) and allows to identify cluster-specific genes using Association Plots. Additionally, APL computes the cluster-specificity scores for all genes which allows to rank the genes by their specificity for a selected cell cluster of interest.

Advisories

None published for Bioconductor

Test coverage

Line coverage

–

Expression

–

Tests / Examples

–

Functions

30 14 exported

Complexity

8.7 avg / 34 max

Call network

30 nodes / 38 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

8,783

Files

73

Compiled share

0%

Has compiled src

No

Language breakdown

R 5,196 (59.2%)Tests 544 (6.2%)Docs 2,581 (29.4%)Vignettes 462 (5.3%)

API

Exported functions

21

Internal functions

16

Recent export changes

v3.20+1 run_APL

Testing

Has tests

Yes

Test-to-code ratio

0.10

testthat edition

3

Docs

Roxygen coverage

95.2%

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

4.4.0

System requirements

–

C++ standard

–

License

GPL (>= 3)

License flags

SPDX valid, OSI approved

History

Versions

9

First release

2022-10-15

Latest release

2026-04-28

Avg cadence

178 days

Cold removal rate

–

Dep drift

5

LOC over versions

v3.15: 7,491 LOCv3.16: 7,491 LOCv3.17: 7,491 LOCv3.18: 7,495 LOCv3.19: 7,973 LOCv3.20: 8,783 LOCv3.21: 8,783 LOCv3.22: 8,783 LOCv3.23: 8,783 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 · 300 wordsVignettesYes · 1 · dynamicNEWSYes · 67% structuredCitation fileNoWebsiteYes · pkgdown
Help pages
37 (1 internal)
Examples that run
100%22 run in a plain check
Exported functions with examples
100%
Documented parameters
100%
Return-value docs
100%
Help pages citing references
27%

Repository practices

Upstream repositoryBeta

5 development-tooling and community-health practices detected across 3 families in the upstream repository

Checks run against github.com/vingronlab/apl on 2026-10-11.

Continuous integration (1)
GitHub Actions
Docs source (3)
pkgdown

GitHub Pages site last deployed 2024-11-04 · The repository has a site deploy workflow

pkgdown site last built 2024-11-04

Lint, format, editor (1)
lintr
How this is detected·Detection ruleset v3 (2026-09-26)

Topics

Maintainer
Clemens Kohl

Available on

CRANr2uBioconductorautoCRANCOPR

People

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("APL")
Kohl, C., Gralinska, E., & Vingron, M. (2026). APL: Association Plots (Version 1.16.0) [Computer software]. https://bioconductor.org/packages/APL

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 APL version 1.16.0 [Data set]. HJJB, LLC. Data release v2026-10-18. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-18, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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