To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("snm")

In most cases, you don't need to download the package archive at all.

snm

   

This package is for version 2.12 of Bioconductor; for the stable, up-to-date release version, see snm.

Supervised Normalization of Microarrays

Bioconductor version: 2.12

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 <brig.mecham at sagebase.org> and John D. Storey <jstorey at princeton.edu>

Maintainer: Brig Mecham <brig.mecham at sagebase.org>

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

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://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 1.8.0
In Bioconductor since BioC 2.8 (R-2.13) (5 years)
License LGPL
Depends R (>= 2.12.0), lme4, splines, corpcor
Imports
LinkingTo
Suggests
SystemRequirements
Enhances
URL
Depends On Me
Imports Me
Suggests Me
Build Report  

Package Archives

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

Package Source snm_1.8.0.tar.gz
Windows Binary snm_1.8.0.zip
Mac OS X 10.6 (Snow Leopard) snm_1.8.0.tgz
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/snm/tree/release-2.12
Package Short Url http://bioconductor.org/packages/snm/
Package Downloads Report Download Stats

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