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1000 Titel
  • Finding Biomarker Signatures in Pooled Sample Designs: A Simulation Framework for Methodological Comparisons
1000 Autor/in
  1. Telaar, Anna |
  2. Nürnberg, Gerd |
  3. Repsilber, Dirk |
1000 Erscheinungsjahr 2010
1000 Art der Datei
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2010-07-04
1000 Erschienen in
1000 Quellenangabe
  • 2010: 318573
1000 FRL-Sammlung
1000 Copyrightjahr
  • 2010
1000 Lizenz
1000 Verlagsversion
  • http://dx.doi.org/10.1155/2010/318573 |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • Detection of discriminating patterns in gene expression data can be accomplished by using various methods of statistical learning. It has been proposed that sample pooling in this context would have negative effects; however, pooling cannot always be avoided. We propose a simulation framework to explicitly investigate the parameters of patterns, experimental design, noise, and choice of method in order to find out which effects on classification performance are to be expected. We use a two-group classification task and simulated gene expression data with independent differentially expressed genes as well as bivariate linear patterns and the combination of both. Our results show a clear increase of prediction error with pool size. For pooled training sets powered partial least squares discriminant analysis outperforms discriminance analysis, random forests, and support vector machines with linear or radial kernel for two of three simulated scenarios. The proposed simulation approach can be implemented to systematically investigate a number of additional scenarios of practical interest.
1000 Fachgruppe
  1. Agrarwissenschaften |
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://frl.publisso.de/adhoc/creator/VGVsYWFyLCBBbm5h|https://frl.publisso.de/adhoc/creator/TsO8cm5iZXJnLCBHZXJk|https://frl.publisso.de/adhoc/creator/UmVwc2lsYmVyLCBEaXJr
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  1. oai:frl.publisso.de:frl:6406250 |
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