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vsn

Variance stabilization and calibration for microarray data


Bioconductor version: Release (3.19)

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.

Author: Wolfgang Huber, with contributions from Anja von Heydebreck. Many comments and suggestions by users are acknowledged, among them Dennis Kostka, David Kreil, Hans-Ulrich Klein, Robert Gentleman, Deepayan Sarkar and Gordon Smyth

Maintainer: Wolfgang Huber <wolfgang.huber at embl.org>

Citation (from within R, enter citation("vsn")):

Installation

To install this package, start R (version "4.4") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("vsn")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("vsn")
Introduction to vsn (HTML version) HTML R Script
Likelihood Calculations for vsn PDF R Script
Verifying and assessing the performance with simulated data PDF
Reference Manual PDF
NEWS Text

Details

biocViews Microarray, OneChannel, Preprocessing, Software, TwoChannel
Version 3.72.0
In Bioconductor since BioC 1.6 (R-2.1) or earlier (> 19 years)
License Artistic-2.0
Depends R (>= 4.0.0), methods, Biobase
Imports affy, limma, lattice, ggplot2
System Requirements
URL http://www.r-project.org http://www.ebi.ac.uk/huber
See More
Suggests affydata, hgu95av2cdf, BiocStyle, knitr, rmarkdown, dplyr, testthat
Linking To
Enhances
Depends On Me cellHTS2, webbioc, rnaseqGene
Imports Me arrayQualityMetrics, autonomics, bnem, DEP, Doscheda, MatrixQCvis, metaseqR2, MSnbase, NormalyzerDE, pvca, tilingArray, ExpressionNormalizationWorkflow, lfproQC, RNAseqQC
Suggests Me adSplit, beadarray, DAPAR, DESeq2, ggbio, GlobalAncova, globaltest, limma, lumi, MsCoreUtils, PAA, QFeatures, qmtools, ribosomeProfilingQC, scp, twilight, estrogen, wrMisc
Links To Me
Build Report Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package vsn_3.72.0.tar.gz
Windows Binary vsn_3.72.0.zip (64-bit only)
macOS Binary (x86_64) vsn_3.72.0.tgz
macOS Binary (arm64) vsn_3.72.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/vsn
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/vsn
Bioc Package Browser https://code.bioconductor.org/browse/vsn/
Package Short Url https://bioconductor.org/packages/vsn/
Package Downloads Report Download Stats