dcanr
Bioc currentDifferential co-expression/association network analysis
Release Lineage
Entered 3.9 · May 3, 2019
Current · Requires R 4.6
Description
This package implements methods and an evaluation framework to infer differential co-expression/association networks. Various methods are implemented and can be evaluated using simulated datasets. Inference of differential co-expression networks can allow identification of networks that are altered between two conditions (e.g., health and disease).
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
51 15 exported
Complexity
2.2 avg / 7 max
Call network
51 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
3,763
Files
87
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
15
Internal functions
36
Recent export changes
Testing & CI
Has tests
Yes
Test-to-code ratio
0.16
testthat edition
–
CI present
Yes
CI type
["github-actions"]
PR gated
Yes
Docs
Roxygen coverage
100%
Health & Security signals
Informational signals; not verdicts.
on.exit coverage
0%
Unsafe pattern score
3
Dep constraint coverage
0%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
3.6.0
System requirements
–
C++ standard
–
License
GPL-3
License flags
SPDX valid, OSI approved
History
Versions
15
First release
2019-05-02
Latest release
2026-04-28
Avg cadence
182 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
- 100%
- Return-value docs
- 100%
- References docs
- 0%
Topics
Depended on by (2)
Bioconductor (2)
People
- Dharmesh D. Bhuva author maintainer