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scLANE

Bioc current

Model Gene Expression Dynamics with Spline-Based NB GLMs, GEEs, & GLMMs

v1.2.0 · software · MIT + file LICENSE

Release Lineage

Entered 3.22 · Oct 30, 2025

Current · Requires R 4.6

1.0 In 2 of 49 releases 3.23

Description

Our scLANE model uses truncated power basis spline models to build flexible, interpretable models of single cell gene expression over pseudotime or latent time. The modeling architectures currently supported are Negative-binomial GLMs, GEEs, & GLMMs. Downstream analysis functionalities include model comparison, dynamic gene clustering, smoothed counts generation, gene set enrichment testing, & visualization.

Test coverage

Line coverage

Expression

Tests / Examples

Functions

57 27 exported

Complexity

12 avg / 83 max

Call network

57 nodes / 53 edges

Test coverage is not measured for Bioconductor packages; nodes fall back to a neutral fill.

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Lowest coverage

Per-function coverage is not measured for this package yet.

Code

Structure

Lines of code

10,833

Files

127

Compiled share

1%

Has compiled src

Yes

Language breakdown

R 7,025 (64.8%)C/C++/src 112 (1%)Tests 610 (5.6%)Docs 2,765 (25.5%)Vignettes 321 (3%)

API

Exported functions

27

Internal functions

23

Recent export changes

v3.22+27 bootstrapRandomEffects, chooseCandidateGenes, clusterGenes +24 more

Testing & CI

Has tests

Yes

Test-to-code ratio

0.09

testthat edition

3

CI present

Yes

CI type

["github-actions"]

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

4.5.0

System requirements

C++ standard

License

MIT + file LICENSE

License flags

SPDX valid, OSI approved

History

Versions

2

First release

2026-03-03

Latest release

2026-04-28

Avg cadence

56 days

Cold removal rate

Dep drift

0

LOC over versions

v3.22: 10,833 LOCv3.23: 10,833 LOC

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

Documentation

Documentation
READMEYes · 1,932 wordsVignettesYes · dynamicpkgdown siteNoNEWSYes · 100% structuredCode of conductYesContributing guideNo
Examples that run
96%
Documented parameters
100%
Return-value docs
100%
References docs
22%

Topics

People

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