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diffuStats

Bioc current

Diffusion scores on biological networks

v1.32.0 · software · GPL-3

Release Lineage

Entered 3.6 · Oct 31, 2017

Current · Requires R 4.6

1.0 In 18 of 49 releases 3.23

Description

Label propagation approaches are a widely used procedure in computational biology for giving context to molecular entities using network data. Node labels, which can derive from gene expression, genome-wide association studies, protein domains or metabolomics profiling, are propagated to their neighbours in the network, effectively smoothing the scores through prior annotated knowledge and prioritising novel candidates. The R package diffuStats contains a collection of diffusion kernels and scoring approaches that facilitates their computation, characterisation and benchmarking.

Test coverage

Line coverage

Expression

Tests / Examples

Functions

50 24 exported

Complexity

3.6 avg / 16 max

Call network

50 nodes / 32 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

10,898

Files

74

Compiled share

2.5%

Has compiled src

Yes

Language breakdown

R 2,455 (22.5%)C/C++/src 274 (2.5%)Tests 993 (9.1%)Docs 1,576 (14.5%)Vignettes 5,600 (51.4%)

API

Exported functions

24

Internal functions

16

Recent export changes

v3.6+20 commuteTimeKernel, diffuse, diffuse_grid +17 more

Testing & CI

Has tests

Yes

Test-to-code ratio

0.40

testthat edition

CI present

Yes

CI type

["travis"]

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

3.4

System requirements

1

C++ standard

C++11

License

GPL-3

License flags

SPDX valid, OSI approved

History

Versions

18

First release

2017-10-30

Latest release

2026-04-28

Avg cadence

182 days

Cold removal rate

Dep drift

1

LOC over versions

v3.6: 10,541 LOCv3.7: 10,553 LOCv3.8: 10,553 LOCv3.9: 10,552 LOCv3.10: 10,552 LOCv3.11: 10,552 LOCv3.12: 10,898 LOCv3.13: 10,898 LOCv3.14: 10,898 LOCv3.15: 10,898 LOCv3.16: 10,898 LOCv3.17: 10,898 LOCv3.18: 10,898 LOCv3.19: 10,898 LOCv3.20: 10,898 LOCv3.21: 10,898 LOCv3.22: 10,898 LOCv3.23: 10,898 LOC

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

Documentation

Documentation
READMEYes · 315 wordsVignettesYes · dynamicpkgdown siteNoNEWSYes · 67% structuredCode of conductNoContributing guideNo
Examples that run
100%
Documented parameters
87%
Return-value docs
100%
References docs
18%

Topics

People

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("diffuStats")
Picart-Armada, S., & Perera-Lluna, A. (2026). diffuStats: Diffusion scores on biological networks (Version 1.32.0) [Computer software]. https://bioconductor.org/packages/diffuStats

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 diffuStats version 1.32.0 [Data set]. HJJB, LLC. Data release v2026-08-23. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-23, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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