title: Comparison of SNP-based and gene-based association studies in detecting rare variants using unrelated individuals.
abstract: We compare the SNP-based and gene-based association studies using 697 unrelated individuals. The Benjamini-Hochberg procedure was applied to control the false discovery rate for all the multiple comparisons. We use a linear model for the single-nucleotide polymorphism (SNP) based association study. For the gene-based study, we consider three methods. The first one is based on a linear model, the second is similarity based, and the third is a new two-step procedure. The results of power using a subset of SNPs show that the SNP-based association test is more powerful than the gene-based ones. However, in some situations, a gene-based study is able to detect the associated variants that were neglected in a SNP-based study. Finally, we apply these methods to a replicate of the quantitative trait Q1 and the binary trait D (D = 1, affected; D = 0, unaffected) for a genome-wide gene search.
authors.affiliation: Department of Mathematics and Statistics, Loyola University, Chicago, IL 60626, USA. ltong@luc.edu.
authors.forename: Liping
authors.initials: L
authors.lastname: Tong
authors.forename: Bamidele
authors.initials: B
authors.lastname: Tayo
authors.forename: Jie
authors.initials: J
authors.lastname: Yang
authors.forename: Richard S
authors.initials: RS
authors.lastname: Cooper