Date of Award
1-2011
Degree Type
Thesis
Degree Name
Master of Science (MS)
Department
Statistics
Supervisor
Narayanaswamy Balakrishnan
Co-Supervisor
Changchun Xie
Language
English
Abstract
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.
Recommended Citation
Qin, Maochang, "Variable Selection Methods for Population-based Genetic Association Studies: SPLS and HSIC" (2011). Open Access Dissertations and Theses. Paper 4312.
http://digitalcommons.mcmaster.ca/opendissertations/4312
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