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

snm

Supervised Normalization of Microarrays

Bioconductor version: 2.13

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 <jstorey at princeton.edu>

Maintainer: John D. Storey <jstorey at princeton.edu>

Installation

To install this package, start R and enter:

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

Documentation

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

browseVignettes("snm")

 

PDF	R Script	snm Tutorial
PDF		Reference Manual
Text		NEWS

Details

biocViews	DifferentialExpression, ExonArray, GeneExpression, Microarray, MultiChannel, MultipleComparisons, OneChannel, Preprocessing, QualityControl, Software, Transcription, TwoChannel
Version	1.10.2
In Bioconductor since	BioC 2.8 (R-2.13)
License	LGPL
Depends	R (>= 2.12.0)
Imports	corpcor, lme4 (>= 1.0), splines
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Package Archives

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

Package Source	snm_1.10.2.tar.gz
Windows Binary	snm_1.10.2.zip (32- & 64-bit)
Mac OS X 10.6 (Snow Leopard)	snm_1.10.2.tgz
Browse/checkout source	(username/password: readonly)
Package Downloads Report	Download Stats