Package: sva
Title: Surrogate Variable Analysis
Version: 3.10.0
Author: Jeffrey T. Leek <jleek@jhsph.edu>, W. Evan Johnson
        <wej@bu.edu>, Hilary S. Parker <hiparker@jhsph.edu>, Andrew E.
        Jaffe <ajaffe@jhsph.edu>, John D. Storey
        <jstorey@princeton.edu>,
Description: The sva package contains functions for removing batch
        effects and other unwanted variation in high-throughput
        experiment. Specifically, the sva package contains functions
        for the identifying and building surrogate variables for
        high-dimensional data sets. Surrogate variables are covariates
        constructed directly from high-dimensional data (like gene
        expression/RNA sequencing/methylation/brain imaging data) that
        can be used in subsequent analyses to adjust for unknown,
        unmodeled, or latent sources of noise. The sva package can be
        used to remove artifacts in two ways: (1) identifying and
        estimating surrogate variables for unknown sources of variation
        in high-throughput experiments (Leek and Storey 2007 PLoS
        Genetics,2008 PNAS) and (2) directly removing known batch
        effects using ComBat (Johnson et al. 2007 Biostatistics).
        Removing batch effects and using surrogate variables in
        differential expression analysis have been shown to reduce
        dependence, stabilize error rate estimates, and improve
        reproducibility, see (Leek and Storey 2007 PLoS Genetics, 2008
        PNAS or Leek et al. 2011 Nat. Reviews Genetics). Surrogate
        variable analysis and ComBat were developed in the context of
        microarray experiments, but may be used as a general tool for
        high throughput data sets where dependence may be involved.
Maintainer: Jeffrey T. Leek <jleek@jhsph.edu>
Depends: R (>= 2.8), corpcor, mgcv
Imports: graphics, stats
Suggests: limma,pamr,bladderbatch
License: Artistic-2.0
biocViews: Microarray, StatisticalMethod, Preprocessing,
        MultipleComparison
Packaged: 2014-04-12 09:43:40 UTC; biocbuild
Built: R 3.1.0; i386-w64-mingw32; 2014-04-12 17:32:00 UTC; windows
Archs: i386, x64
