To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("vsn")
In most cases, you don't need to download the package archive at all.
vsn
Variance stabilization and calibration for microarray data
Bioconductor version: 3.0
The package implements a method for normalising microarray intensities, both between colours within array, and between arrays. The method uses a robust variant of the maximum-likelihood estimator for the stochastic model of microarray data described in the references (see vignette). The model incorporates data calibration (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 <huber at ebi.ac.uk>
Citation (from within R,
enter citation("vsn")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("vsn")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("vsn")
| R Script | Introduction to vsn | |
| R Script | Likelihood Calculations for vsn | |
| R Script | Verifying and assessing the performance with simulated data | |
| Reference Manual |
Details
| biocViews | Microarray, OneChannel, Preprocessing, Software, TwoChannel |
| Version | 3.34.0 |
| In Bioconductor since | BioC 1.6 (R-2.1) or earlier |
| License | Artistic-2.0 |
| Depends | R (>= 2.10), Biobase(>= 2.5.5) |
| Imports | methods, affy(>= 1.23.4), limma, lattice |
| LinkingTo | |
| Suggests | affydata, hgu95av2cdf |
| SystemRequirements | |
| Enhances | |
| URL | http://www.r-project.org http://www.ebi.ac.uk/huber |
| Depends On Me | affyPara, cellHTS2, MmPalateMiRNA, webbioc |
| Imports Me | arrayQualityMetrics, imageHTS, LVSmiRNA, metaseqR, MSnbase, pvca, Ringo, tilingArray |
| Suggests Me | adSplit, beadarray, BiocCaseStudies, cellHTS, DESeq, DESeq2, estrogen, ggbio, GlobalAncova, globaltest, limma, lumi, PAA, twilight |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | vsn_3.34.0.tar.gz |
| Windows Binary | vsn_3.34.0.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | vsn_3.34.0.tgz |
| Mac OS X 10.9 (Mavericks) | vsn_3.34.0.tgz |
| Browse/checkout source | (username/password: readonly) |
| Package Downloads Report | Download Stats |
Common Bioconductor workflows include:
- Oligonucleotide Arrays
- High-throughput Sequencing
- Counting Reads for Differential Expression (parathyroideSE vignette)
- Annotation
- Annotating Variants
- Annotating Ranges
- Flow Cytometry and other assays
- Candidate Binding Sites for Known Transcription Factors
- Cloud-enabled cis-eQTL search and annotation
- RNA-Seq workflow: gene-level exploratory analysis and differential expression
- Changing genomic coordinate systems with rtracklayer::liftOver
- Mass spectrometry and proteomics data analysis
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