Statistical Studies of Genomics Data
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Date
2004-12-28
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Abstract
In recent years, studies on Genetics and Genomics have become one of the most active fields in science. The Genetic and Genomics data have several significant and unique characteristics that bring great challenges for data analysis. Three statistical studies have been presented in this dissertation. In chapter 1, an empirical Bayesian approach has been developed in a linear mixed model for Microarray data analysis. In chapter 2, a multiple order Markov chain model is applied to summarize the local correlation patterns among multiple genetic markers in linkage disequilibrium mapping. In chapter 3, a shrinkage method is being developed to integrate Biological prior knowledge presented in moment statistics. This new method may be useful in some genetic network studies.
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Microarray Data Analysis, Shrinkage method, Linkage Disequilibrium Mapping
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Degree
PhD
Discipline
Statistics
