Statistical methods for microarray data

Leiden Repository

Statistical methods for microarray data

Type: Doctoral Thesis
Title: Statistical methods for microarray data
Author: Goeman, Jelle Jurjen
Publisher: Medical Statistics and Bio Informatics, LUMC, Mathematical Institute, Leiden University
Issue Date: 2006-03-08
Keywords: Statistics
Microarray data
Pathway analysis
Hypothesis testing
Abstract: In this thesis novel statistical methods are developed for the analysis of high dimensional microarray data. In short: Chapter 1 gives an overview of the most important research methods developed so far. Chapter 2 describes a method for testing association of the expression of gene sets (pathways) with a patient level response variable, which can be continuous or two-valued. Chapter 3 extends the methodology of chapter 2 to survival as a response variable. Chapter 4 presents a goodness-of-fit test for the multinomial regression model, which can be used to extend the methodology of chapter 2 to multi-valued outcomes. Chapter 5 presents a general theoretical framework in for the tests of chapters 2-4 and derives optimality properties for these tests. Chapter 6 presents a method for predicting a response variable from high dimensional data, based on latent variables. Chapter 7 presents a visualization tool for improved presentation of scatterplots with many thousands of dots.
Description: Promotores: J.C. van Houwelingen, S.A. van de Geer.
With summary in Dutch
Faculty: LUMC
Citation: Goeman,J.J., 2006, Doctoral thesis, Leiden University
ISBN: 9789090203720

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application/pdf Title page_Contents 466.0Kb View/Open
application/pdf Chapter 1 137.5Kb View/Open
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application/pdf Chapter 3 242.6Kb View/Open
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application/pdf Chapter 5 253.6Kb View/Open
application/pdf Chapter 6 272.7Kb View/Open
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application/pdf Chapter 8 84.19Kb View/Open
application/pdf Appendix 667.0Kb View/Open
application/pdf Summary in Dutch_Bibliography_CV 120.5Kb View/Open
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