| Boulesteix, Anne-Laure and Strimmer, Korbinian (2005): Partial Least Squares: A Versatile Tool for the Analysis of High-Dimensional Genomic Data. Collaborative Research Center 386, Discussion Paper 457 |
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193Kb |
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.
| Item Type: | Paper (Research Paper) |
|---|---|
| Collections: | Mathematics, Computer Science and Statistics > Statistics > Collaborative Research Center 386 Special Research Fields > Special Research Field 386 |
| Subjects: | 500 Science > 510 Mathematics |
| URN: | urn:nbn:de:bvb:19-epub-1826-2 |
| Language: | English |
| ID Code: | 1826 |
| Deposited On: | 11. Apr 2007 |
| Last Modified: | 08. Jan 2013 15:56 |
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