DEsubs
Bioc currentDEsubs: an R package for flexible identification of differentially expressed subpathways using RNA-seq expression experiments
Release Lineage
Entered 3.4 · Oct 18, 2016
Current · Requires R 4.6
Description
DEsubs is a network-based systems biology package that extracts disease-perturbed subpathways within a pathway network as recorded by RNA-seq experiments. It contains an extensive and customizable framework covering a broad range of operation modes at all stages of the subpathway analysis, enabling a case-specific approach. The operation modes refer to the pathway network construction and processing, the subpathway extraction, visualization and enrichment analysis with regard to various biological and pharmacological features. Its capabilities render it a tool-guide for both the modeler and experimentalist for the identification of more robust systems-level biomarkers for complex diseases.
None published for Bioconductor
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
40 0 exported
Complexity
7.9 avg / 37 max
Call network
40 nodes / 61 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
4,055
Files
43
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
6
Internal functions
40
Testing
Has tests
Yes
Test-to-code ratio
0.00
testthat edition
–
Docs
Roxygen coverage
0%
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-3
License flags
SPDX valid, OSI approved
History
Versions
20
First release
2017-04-07
Latest release
2026-04-28
Avg cadence
181 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
- Help pages
- 6
- Examples that run
- 100%6 run in a plain check
- Exported functions with examples
- not tracked
- Documented parameters
- not tracked
- Return-value docs
- not tracked
- Help pages citing references
- 0%
- DEsubs PDF
Repository practices
Checks read the Bioconductor git repository (git.bioconductor.org), branch RELEASE_3_23.
No development-tooling practices detected in the Bioconductor git repository.
Datasets
| Name | Class | Size | Also in |
|---|---|---|---|
| DEsubs.out | list | 5 elements | No other package |
| edgeLists | list | 7 elements | No other package |
| libraryEntrezToExternalNomenclature | list | 6 elements | No other package |
| libraryEntrezToHGNC | vector | 6,883 elements | No other package |
| mRNAexpr | matrix | 6,880 × 8 | No other package |
| rankedList | vector | 5,023 elements | No other package |
| targetsPerClass | matrix | 412 × 394 | No other package |
| toyData | data.frame | 5 × 9 | No other package |
Topics
People (from the free-text Author field)
Cite
Cite this package
Run in R for the authors' entry:
citation("DEsubs")The package provides a citation file, so citation() returns the authors' own entry.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-26, which the citation names so these numbers can be found later. More on citing and the projects behind them.