snm

Supervised Normalization of Microarrays

Bioconductor version: Development (2.8)

SNM is a modeling strategy especially designed for normalizing high-throughput genomic data. The underlying premise of our approach is that your data is a function of what we refer to as study-specific variables. These variables are either biological variables that represent the target of the statistical analysis, or adjustment variables that represent factors arising from the experimental or biological setting the data is drawn from. The SNM approach aims to simultaneously model all study-specific variables in order to more accurately characterize the biological or clinical variables of interest.

Author: Brig Mecham and John D. Storey

Maintainer: Brig Mecham

To install this package, start R and enter:

source("http:///biocLite.R")
biocLite("snm")    

Documentation

PDF

R Script

snm Tutorial

Reference Manual

Details

biocViews	Microarray, OneChannel, TwoChannel, MultiChannel, DifferentialExpression, ExonArray, GeneExpression, Transcription, MultipleComparisons, Preprocessing, QualityControl
Depends	R, lme4, splines, corpcor
Imports
Suggests
System Requirements
License	LGPL
URL
Depends On Me
Imports Me
Suggests Me
Version	0.99.0

Package Downloads

Package Source	snm_0.99.0.tar.gz
Windows Binary	snm_0.99.0.zip (32- & 64-bit)
MacOS 10.5 (Leopard) binary	snm_0.99.0.tgz
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