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MODA

Bioc current

MODA: MOdule Differential Analysis for weighted gene co-expression network

v1.38.0 · Package record · software · GPL (>= 2)

Release Lineage

Entered 3.4 · Oct 18, 2016

Current · Requires R 4.6

1.0 In 20 of 49 releases 3.23

Description

MODA can be used to estimate and construct condition-specific gene co-expression networks, and identify differentially expressed subnetworks as conserved or condition specific modules which are potentially associated with relevant biological processes.

Advisories

None published for Bioconductor

Test coverage

Line coverage

–

Expression

–

Tests / Examples

–

Functions

20 9 exported

Complexity

4 avg / 11 max

Call network

20 nodes / 8 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

2,051

Files

27

Compiled share

0%

Has compiled src

No

Language breakdown

R 1,078 (52.6%)Docs 641 (31.3%)Vignettes 332 (16.2%)

API

Exported functions

9

Internal functions

11

Recent export changes

v3.5+5 ModuleFrequency, WeightedModulePartitionAmoutain, WeightedModulePartitionHierarchical +2 more  −1 WeightedModulePartitionDensity

Testing

Has tests

No

Test-to-code ratio

0.00

testthat edition

–

Docs

Roxygen coverage

100%

Health & Security signals

Informational signals; not verdicts.

on.exit coverage

0%

Unsafe pattern score

0

Dep constraint coverage

0%

Secret pattern count

0

Bundled 3rd-party code

2 items

Portability & License

Min R version

3.3

System requirements

–

C++ standard

–

License

GPL (>= 2)

License flags

SPDX valid, OSI approved

History

Versions

20

First release

2016-10-17

Latest release

2026-04-28

Avg cadence

182 days

Cold removal rate

100%

Dep drift

7

LOC over versions

v3.4: 742 LOCv3.5: 2,051 LOCv3.6: 2,051 LOCv3.7: 2,051 LOCv3.8: 2,051 LOCv3.9: 2,051 LOCv3.10: 2,051 LOCv3.11: 2,051 LOCv3.12: 2,051 LOCv3.13: 2,051 LOCv3.14: 2,051 LOCv3.15: 2,051 LOCv3.16: 2,051 LOCv3.17: 2,051 LOCv3.18: 2,051 LOCv3.19: 2,051 LOCv3.20: 2,051 LOCv3.21: 2,051 LOCv3.22: 2,051 LOCv3.23: 2,051 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
READMENoVignettesYes · 1 · dynamicNEWSYes · 0% structuredCitation fileNoWebsitenot declared in DESCRIPTION
Help pages
16
Examples that run
100%10 run in a plain check
Exported functions with examples
89%
Documented parameters
100%
Return-value docs
100%
Help pages citing references
44%
Vignettes (1)

Repository practices

Bioconductor git repository

Checks read the Bioconductor git repository (git.bioconductor.org), branch RELEASE_3_23.

No development-tooling practices detected in the Bioconductor git repository.

Datasets

Bundled datasets · 2
NameClassSizeAlso in
datExpr1matrix20 × 500No other package
datExpr2matrix25 × 500No other package

All of MODA's data objects

Topics

Maintainer
Dong Li

Available on

CRANr2uBioconductorautoCRANCOPR

People (from the free-text Author field)

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("MODA")

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 MODA version 1.38.0 [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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