variancePartition
Bioc currentQuantify and interpret drivers of variation in multilevel gene expression experiments
Release Lineage
Entered 3.2 · Oct 14, 2015
Current · Requires R 4.6
Description
Quantify and interpret multiple sources of biological and technical variation in gene expression experiments. Uses a linear mixed model to quantify variation in gene expression attributable to individual, tissue, time point, or technical variables. Includes dream differential expression analysis for repeated measures.
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
71 23 exported
Complexity
7.2 avg / 120 max
Call network
71 nodes / 51 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
15,121
Files
608
Compiled share
0%
Has compiled src
No
Language breakdown
API
Exported functions
38
Internal functions
48
Recent export changes
Testing & CI
Has tests
Yes
Test-to-code ratio
0.00
testthat edition
–
CI present
No
CI type
[]
PR gated
No
Docs
Roxygen coverage
100%
Health & Security signals
Informational signals; not verdicts.
on.exit coverage
25%
Unsafe pattern score
0
Dep constraint coverage
17.2%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
4.3.0
System requirements
–
C++ standard
–
License
GPL-2
License flags
SPDX valid, OSI approved
History
Versions
22
First release
2016-03-03
Latest release
2026-04-28
Avg cadence
194 days
Cold removal rate
100%
Dep drift
30
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
- 97%
- Return-value docs
- 84%
- References docs
- 6%
Topics
Depended on by (6)
People
- Gabriel Hoffman author maintainer
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("variancePartition")This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-08-22, which the citation names so these numbers can be found later. More on citing and the projects behind them.