DNEA
Bioc currentDifferential Network Enrichment Analysis for Biological Data
Release Lineage
Entered 3.22 · Oct 30, 2025
Current · Requires R 4.6
Description
The DNEA R package is the latest implementation of the Differential Network Enrichment Analysis algorithm and is the successor to the Filigree Java-application described in Iyer et al. (2020). The package is designed to take as input an m x n expression matrix for some -omics modality (ie. metabolomics, lipidomics, proteomics, etc.) and jointly estimate the biological network associations of each condition using the DNEA algorithm described in Ma et al. (2019). This approach provides a framework for data-driven enrichment analysis across two experimental conditions that utilizes the underlying correlation structure of the data to determine feature-feature interactions.
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
93 12 exported
Complexity
3.4 avg / 16 max
Call network
93 nodes / 47 edges
Test coverage is not measured for Bioconductor packages; nodes fall back to a neutral fill.
Call graph
Open call graph →Lowest coverage
Per-function coverage is not measured for this package yet.
Code
Structure
Lines of code
10,483
Files
91
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
35
Internal functions
81
Recent export changes
Testing & CI
Has tests
Yes
Test-to-code ratio
0.03
testthat edition
3
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
7.7%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
4.2
System requirements
–
C++ standard
–
License
MIT + file LICENSE
License flags
SPDX valid, OSI approved
History
Versions
2
First release
2025-10-29
Latest release
2026-04-28
Avg cadence
181 days
Cold removal rate
–
Dep drift
0
LOC over versions
Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.
Documentation
- Examples that run
- 100%
- Documented parameters
- 99%
- Return-value docs
- 100%
- References docs
- 17%
Topics
People
- Christopher Patsalis maintainer author
- Gayatri Iyer author
- Alla Karnovsky fnd
- George Michailidis fnd