title: Eigen-R2 for dissecting variation in high-dimensional studies.
abstract: We provide a new statistical algorithm and software package called 'eigen-R(2)' for dissecting the variation of a high-dimensional biological dataset with respect to other measured variables of interest. We apply eigen-R(2) to two real-life examples and compare it with simply averaging R(2) over many features.
  
  
  BACKGROUND
  An R-package eigenR2 is available at http://www.genomine.org/eigenr2/ and will be made publicly available via Bioconductor.
authors: Lewis-Sigler Institute and Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA.
authors: Lin S
authors: LS
authors: Chen
authors: John D
authors: JD
authors: Storey
mesh_terms: D000465:Algorithms; D020869:Gene Expression Profiling; D014644:Genetic Variation; D015233:Models, Statistical; D012984:Software