vsn
Bioc currentVariance stabilization and calibration for microarray data
Release Lineage
Entered 1.4 · May 17, 2004
Current · Requires R 4.6
Description
The package implements a method for normalising microarray intensities from single- and multiple-color arrays. It can also be used for data from other technologies, as long as they have similar format. The method uses a robust variant of the maximum-likelihood estimator for an additive-multiplicative error model and affine calibration. The model incorporates data calibration step (a.k.a. normalization), a model for the dependence of the variance on the mean intensity and a variance stabilizing data transformation. Differences between transformed intensities are analogous to "normalized log-ratios". However, in contrast to the latter, their variance is independent of the mean, and they are usually more sensitive and specific in detecting differential transcription.
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
53 7 exported
Complexity
5.3 avg / 22 max
Call network
53 nodes / 50 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
5,027
Files
59
Compiled share
21.8%
Has compiled src
Yes
Language breakdown
API
Exported functions
7
Internal functions
30
Recent export changes
Testing & CI
Has tests
Yes
Test-to-code ratio
0.01
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
–
Unsafe pattern score
0
Dep constraint coverage
0%
Secret pattern count
0
Bundled 3rd-party code
2 items
Portability & License
Min R version
4.0.0
System requirements
–
C++ standard
–
License
Artistic-2.0
License flags
SPDX valid, OSI approved
History
Versions
45
First release
2004-08-23
Latest release
2026-04-28
Avg cadence
182 days
Cold removal rate
100%
Dep drift
12
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
- 90%
- Return-value docs
- 100%
- References docs
- 31%
Topics
Depended on by (50)
Bioconductor (48)
People
- Wolfgang Huber author maintainer
- Federal Ministry of Research, Technology and Space of Germany, DHGP fnd
- Robert Gentleman contributor
- Hans-Ulrich Klein contributor
- Dennis Kostka contributor
- David Kreil contributor
- Deepayan Sarkar contributor
- Gordon Smyth contributor
- Anja von Heydebreck author
Cite
Cite this package
Run in R for the authors' preferred citation:
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Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
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