Eigen-$R^2$ 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.

Publication
Bioinformatics, 24 (19): 2260–2262
DOI
10.1093/bioinformatics/btn411
Date
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