Date of Award
7-17-2009
Degree Type
Thesis
Degree Name
Master of Science (MS)
Department
Mathematics and Statistics
First Advisor
Dr. Yixin Fang - Chair
Second Advisor
Dr. Yuanhui Xiao
Third Advisor
Dr. Yu-Sheng Hsu
Abstract
Genome-wide Association (GWA) studies have become a widely used method for analyzing genetic data. It is useful in detecting associations that may exist between particular alleles and diseases of interest. This thesis investigates the dataset provided from problem 1 of the Genetic Analysis Workshop 16 (GAW 16). The dataset consists of GWA data from the North American Rheumatoid Arthritis Consortium (NARAC). The thesis attempts to determine a set of single nucleotide polymorphisms (SNP) that are associated significantly with rheumatoid arthritis. Moreover, this thesis also attempts to address the question of whether the one-sided alternative hypothesis that the minor allele is positively associated with the disease or the two-sided alternative hypothesis that the genotypes at a locus are associated with the disease is appropriate, or put another way, the question of whether examining both alternative hypotheses yield more information.
DOI
https://doi.org/10.57709/1059730
Recommended Citation
Scott, Nigel A., "An Application of Armitage Trend Test to Genome-wide Association Studies." Thesis, Georgia State University, 2009.
doi: https://doi.org/10.57709/1059730