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Bioinformatics Advance Access originally published online on August 20, 2008
Bioinformatics 2008 24(19):2260-2262; 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 and 2Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA

*To whom correspondence should be addressed.


  Abstract

Summary: We provide a new statistical algorithm and software package called ‘eigen-R2’ for dissecting the variation of a high-dimensional biological dataset 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

Supplementary information: Supplementary data are available at Bioinformatics online.

Associate Editor: Joaquin Dopazo

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

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