Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/31043 
Year of Publication: 
2005
Series/Report no.: 
Discussion Paper No. 457
Publisher: 
Ludwig-Maximilians-Universität München, Sonderforschungsbereich 386 - Statistische Analyse diskreter Strukturen, München
Abstract: 
Partial Least Squares (PLS) is a highly efficient statistical regression technique that is well suited for the analysis of high-dimensional genomic data. In this paper we review the theory and applications of PLS both under methodological and biological points of view. Focusing on microarray expression data we provide a systematic comparison of the PLS approaches currently employed, and discuss problems as different as tumor classification, identification of relevant genes, survival analysis and modeling of gene networks.
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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