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Bioinformatics Advance Access published online on August 20, 2008
Bioinformatics, doi:10.1093/bioinformatics/btn411
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© The Author (2008). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Eigen-R2 for Dissecting Variation in High-dimensional Studies

Lin S. Chen 1 and John D. Storey 1,2

1Lewis-Sigler Institute, Princeton University, Princeton, NJ 08544, USA
2Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA

*To whom correspondence should be addressed. Dr. John D. Storey, E-mail: jstorey{at}princeton.edu


  Abstract

Summary: We provide a new statistical algorithm and software package called "eigen-R2" for dissecting the variation of a highdimensional biological data set with respect to other measured variables of interest. We apply eigen-R2 to two real-life examples and compare it with simply averaging R2 over many features.

Availability: An R-package eigenR2 is available at http://www.genomine.org/eigenr2/ and will be made publicly available via Bioconductor.

Contact: jstorey{at}princeton.edu

Associate Editor: Dr. Joaquin Dopazo

Received on March 18, 2008; revised on June 3, 2008; accepted on August 1, 2008

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