decoupleR
Bioc currentdecoupleR: Ensemble of computational methods to infer biological activities from omics data
Release Lineage
Entered 3.13 · May 20, 2021
Current · Requires R 4.6
Description
Many methods allow us to extract biological activities from omics data using information from prior knowledge resources, reducing the dimensionality for increased statistical power and better interpretability. Here, we present decoupleR, a Bioconductor package containing different statistical methods to extract these signatures within a unified framework. decoupleR allows the user to flexibly test any method with any resource. It incorporates methods that take into account the sign and weight of network interactions. decoupleR can be used with any omic, as long as its features can be linked to a biological process based on prior knowledge. For example, in transcriptomics gene sets regulated by a transcription factor, or in phospho-proteomics phosphosites that are targeted by a kinase.
None published for Bioconductor
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
63 29 exported
Complexity
1.8 avg / 9 max
Call network
63 nodes / 75 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
7,049
Files
108
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
43
Internal functions
34
Testing
Has tests
Yes
Test-to-code ratio
0.18
testthat edition
3
Docs
Roxygen coverage
97.7%
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
4.0
System requirements
–
C++ standard
–
License
GPL-3 + file LICENSE
License flags
SPDX valid, OSI approved
History
Versions
11
First release
2021-05-19
Latest release
2026-04-28
Avg cadence
179 days
Cold removal rate
100%
Dep drift
5
LOC over versions
Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/bioc-code-metrics.
Documentation
- Help pages
- 36 (8 internal)includes a package overview page
- Examples that run
- 91%29 run in a plain check · 3 never run
- Exported functions with examples
- 97%
- Documented parameters
- 96%
- Return-value docs
- 63%
- Help pages citing references
- 0%
Repository practices
8 development-tooling and community-health practices detected across 4 families in the upstream repository
Checks run against github.com/saezlab/decoupler on 2026-10-21.
The R CMD check workflow runs on Linux, macOS and Windows, and on R-devel
GitHub Pages site last deployed 2024-10-19 · The repository has a site deploy workflow
pkgdown site last built 2024-10-19
Datasets
Topics
Depended on by (7)
Suggested by (1)
People
- Pau Badia-i-Mompel author maintainer
- Jana Braunger author
- Daniel Dimitrov author
- Aurélien Dugourd author
- Celina Geiss author
- Christian H. Holland author
- Sophia Müller-Dott author
- Ricardo O. Ramirez Flores author
- Julio Saez-Rodriguez author
- Petr Taus author
- Jesús Vélez-Santiago author
Cite
Cite this package
Run in R for the authors' entry:
citation("decoupleR")The package provides a citation file, so citation() returns the authors' own entry.
It points to 10.1093/bioadv/vbac016.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-25, which the citation names so these numbers can be found later. More on citing and the projects behind them.