Bioconductor version: Release (3.14)
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")
):
To install this package, start R (version "4.1") 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.
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("vsn")
HTML | R Script | Introduction to vsn (HTML version) |
R Script | Likelihood Calculations for vsn | |
Verifying and assessing the performance with simulated data | ||
Reference Manual | ||
Text | NEWS |
biocViews | Microarray, OneChannel, Preprocessing, Software, TwoChannel |
Version | 3.62.0 |
In Bioconductor since | BioC 1.6 (R-2.1) or earlier (> 17 years) |
License | Artistic-2.0 |
Depends | R (>= 4.0.0), methods, Biobase |
Imports | affy, limma, lattice, ggplot2 |
LinkingTo | |
Suggests | affydata, hgu95av2cdf, BiocStyle, knitr, rmarkdown, dplyr, testthat |
SystemRequirements | |
Enhances | |
URL | http://www.r-project.org http://www.ebi.ac.uk/huber |
Depends On Me | affyPara, cellHTS2, rnaseqGene, webbioc |
Imports Me | arrayQualityMetrics, bnem, coexnet, DAPAR, DEP, Doscheda, ExpressionNormalizationWorkflow, imageHTS, MatrixQCvis, metaseqR2, MSnbase, NormalyzerDE, pvca, Ringo, tilingArray |
Suggests Me | adSplit, beadarray, DESeq2, estrogen, flowVS, ggbio, GlobalAncova, globaltest, limma, lumi, MsCoreUtils, PAA, QFeatures, scp, twilight |
Links To Me | |
Build Report |
Follow Installation instructions to use this package in your R session.
Source Package | vsn_3.62.0.tar.gz |
Windows Binary | vsn_3.62.0.zip |
macOS 10.13 (High Sierra) | vsn_3.62.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/vsn |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/vsn |
Package Short Url | https://bioconductor.org/packages/vsn/ |
Package Downloads Report | Download Stats |
Old Source Packages for BioC 3.14 | Source Archive |
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