pairedGSEA
Bioc currentPaired DGE and DGS analysis for gene set enrichment analysis
Release Lineage
Entered 3.17 · Apr 26, 2023
Current · Requires R 4.6
Description
pairedGSEA makes it simple to run a paired Differential Gene Expression (DGE) and Differencital Gene Splicing (DGS) analysis. The package allows you to store intermediate results for further investiation, if desired. pairedGSEA comes with a wrapper function for running an Over-Representation Analysis (ORA) and functionalities for plotting the results.
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
31 4 exported
Complexity
4.2 avg / 23 max
Call network
31 nodes / 37 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
3,361
Files
41
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
4
Internal functions
27
Testing & CI
Has tests
Yes
Test-to-code ratio
0.49
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
0%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
4.4.0
System requirements
–
C++ standard
–
License
MIT + file LICENSE
License flags
SPDX valid, OSI approved
History
Versions
7
First release
2023-04-25
Latest release
2026-04-28
Avg cadence
182 days
Cold removal rate
–
Dep drift
2
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
People
- Søren Helweg Dam maintainer author
- Lars Rønn Olsen author
- Kristoffer Vitting-Seerup author