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Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/9165
Title: Variable Selection Methods for Population-based Genetic Association Studies: SPLS and HSIC
Authors: Qin, Maochang
Advisor: Balakrishnan, Narayanaswamy
Xie, Changchun
Department: Statistics
Keywords: Statistics and Probability;Statistics and Probability
Publication Date: 2011
Abstract: <p>This project aims to identify the single nucleotide polymorphisms(SNPs), which are associated with the muscle size and strength in Caucasian. Two methods sparse partial least squares (SPLS) and sparse Hilbert-Schmidt independence criterion (HSIC) were applied for dimension reduction and variables selection in the Functional SNPs Associated with Muscle Size and Strength(FAMuss) Study. The selection ability of two methods was compared by simulations. The genetic determinants of skeletal muscle size and strength before and after exercise training in Caucasian were selected by using these two methods.</p>
URI: http://hdl.handle.net/11375/9165
Identifier: opendissertations/4312
5330
2039571
Appears in Collections:Open Access Dissertations and Theses

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