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DEGraph

Bioc current

Two-sample tests on a graph

v1.64.0 · software · GPL-3

Release Lineage

Entered 2.7 · Oct 18, 2010

Current · Requires R 4.6

1.0 In 32 of 49 releases 3.23

Description

DEGraph implements recent hypothesis testing methods which directly assess whether a particular gene network is differentially expressed between two conditions. This is to be contrasted with the more classical two-step approaches which first test individual genes, then test gene sets for enrichment in differentially expressed genes. These recent methods take into account the topology of the network to yield more powerful detection procedures. DEGraph provides methods to easily test all KEGG pathways for differential expression on any gene expression data set and tools to visualize the results.

Test coverage

Line coverage

Expression

Tests / Examples

Functions

14 14 exported

Complexity

10.6 avg / 27 max

Call network

14 nodes / 6 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

61,698

Files

56

Compiled share

0%

Has compiled src

No

Language breakdown

R 2,006 (3.3%)Docs 1,322 (2.1%)Vignettes 58,370 (94.6%)

API

Exported functions

14

Internal functions

0

Testing & CI

Has tests

No

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

2.10.0

System requirements

C++ standard

License

GPL-3

License flags

SPDX valid, OSI approved

History

Versions

32

First release

2010-10-18

Latest release

2026-04-28

Avg cadence

183 days

Cold removal rate

Dep drift

1

LOC over versions

v2.7: 3,265 LOCv2.8: 3,390 LOCv2.9: 3,322 LOCv2.10: 3,322 LOCv2.11: 3,328 LOCv2.12: 3,328 LOCv2.13: 3,328 LOCv2.14: 61,698 LOCv3.0: 61,698 LOCv3.1: 61,698 LOCv3.2: 61,698 LOCv3.3: 61,698 LOCv3.4: 61,698 LOCv3.5: 61,698 LOCv3.6: 61,698 LOCv3.7: 61,698 LOCv3.8: 61,698 LOCv3.9: 61,698 LOCv3.10: 61,698 LOCv3.11: 61,698 LOCv3.12: 61,698 LOCv3.13: 61,698 LOCv3.14: 61,698 LOCv3.15: 61,698 LOCv3.16: 61,698 LOCv3.17: 61,698 LOCv3.18: 61,698 LOCv3.19: 61,698 LOCv3.20: 61,698 LOCv3.21: 61,698 LOCv3.22: 61,698 LOCv3.23: 61,698 LOC

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

Documentation

Documentation
READMENoVignettesYes · dynamicpkgdown siteNoNEWSNoCode of conductNoContributing guideNo
Examples that run
100%
Documented parameters
99%
Return-value docs
100%
References docs
17%

Topics

People

Laurent Jacob

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("DEGraph")

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 DEGraph version 1.64.0 [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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