Eigen-R-square Software Package
A common goal in the analysis of high-dimensional biological studies is to decompose the variation of thousands of measured features in terms of some other variables. In statistical terminology, the measured features are considered a set of related "response variables" and the other variables used to explain their variation are called "independent variables." A common example of this goal is in dissecting the variation of transcriptional levels of thousands of genes in terms of relevant biological variables, such as genotypes, experimental variables, or clinical variables. Eigen-R-square is a high-dimensional version of the classic R-square statistic. It can be applied when one wants to determine the aggregate R-square value for many related response variables according to a common set of independent variables. This is a generalization of simply taking the mean R-square values. The eigenR2 package implements this method in a user friendly manner.
The eigenR2 package can be downloaded:
- Chen LS and Storey JD. (2007) Eigen-R-square for dissecting variation in high-dimensional studies. Submitted.
- User manual
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