SNM is a modeling strategy especially designed for normalizing highthroughput genomic data. The underlying premise of our approach is that your data is a function of what we refer to as studyspecific 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 studyspecific variables in order to more accurately characterize the biological or clinical variables of interest.
Package details 


Author  Brig Mecham and John D. Storey <jstorey@princeton.edu> 
Bioconductor views  DifferentialExpression ExonArray GeneExpression Microarray MultiChannel MultipleComparison OneChannel Preprocessing QualityControl Transcription TwoChannel 
Maintainer  John D. Storey <jstorey@princeton.edu> 
License  LGPL 
Version  1.38.0 
Package repository  View on Bioconductor 
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