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

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Author(s): Cangelosi Richard | Goriely Alain

Journal: Biology Direct
ISSN 1745-6150

Volume: 2;
Issue: 1;
Start page: 2;
Date: 2007;
Original page

ABSTRACT
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. This article was reviewed by Orly Alter, John Spouge (nominated by Eugene Koonin), David Horn and Roy Varshavsky (both nominated by O. Alter).
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