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Biol Direct. 2007 Jan 17;2:2.

Component retention in principal component analysis with application to cDNA microarray data.

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1
Program in Applied Mathematics, University of Arizona, Tucson, AZ85721, USA. rcan@math.arizona.edu

Abstract

Shannon entropy is used to provide an estimate of the number of interpretable components in a principal component analysis. In addition, several ad hoc stopping rules for dimension determination are reviewed and a modification of the broken stick model is presented. The modification incorporates a test for the presence of an "effective degeneracy" among the subspaces spanned by the eigenvectors of the correlation matrix of the data set then allocates the total variance among subspaces. A summary of the performance of the methods applied to both published microarray data sets and to simulated data is given.

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