Package: snm
Type: Package
Title: Supervised Normalization of Microarrays
Version: 1.58.0
Author: Brig Mecham and John D. Storey <jstorey@princeton.edu>
Description: 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.
Maintainer: John D. Storey <jstorey@princeton.edu>
Depends: R (>= 2.12.0)
Imports: corpcor, lme4 (>= 1.0), splines
License: LGPL
biocViews: Microarray, OneChannel, TwoChannel, MultiChannel,
        DifferentialExpression, ExonArray, GeneExpression,
        Transcription, MultipleComparison, Preprocessing,
        QualityControl
git_url: https://git.bioconductor.org/packages/snm
git_branch: RELEASE_3_22
git_last_commit: 23a1e16
git_last_commit_date: 2025-10-29
Repository: Bioconductor 3.22
Date/Publication: 2025-10-29
NeedsCompilation: no
Packaged: 2025-10-30 05:32:17 UTC; biocbuild
Built: R 4.5.1; ; 2025-10-30 12:40:42 UTC; unix
