title: Detecting association of rare and common variants by testing an optimally weighted combination of variants with longitudinal data.
abstract: Increasing evidence shows that complex diseases are caused by both common and rare variants. Recently, several statistical methods for detecting associations of rare variants have been developed, including the test for testing the effect of an optimally weighted combination of variants (TOW) developed by our group in 2012. These methodologies consider phenotype measurement at only one time point. Because many sequence data have been developed on population cohorts that contain phenotype measurements at multiple time points, such as the data set provided in the Genetic Analysis Workshop 18 (GAW18), we extend TOW from phenotype measurement at one time point to phenotype measurements at multiple time points. We then apply the newly proposed method to the GAW18 data set and compare the power of the new method with TOW using only one phenotype measurement. The application results show that the newly proposed method jointly modeling phenotype measurements at all time points has increased power over TOW.
authors.affiliation: Department of Mathematical Sciences, Michigan Technological University, 1400 Townsend Drive, Houghton, MI 49931, USA.
authors.forename: Shuaicheng
authors.initials: S
authors.lastname: Wang
authors.affiliation: Department of Mathematical Sciences, Michigan Technological University, 1400 Townsend Drive, Houghton, MI 49931, USA.
authors.forename: Shurong
authors.initials: S
authors.lastname: Fang
authors.affiliation: Department of Mathematical Sciences, Michigan Technological University, 1400 Townsend Drive, Houghton, MI 49931, USA.
authors.forename: Qiuying
authors.initials: Q
authors.lastname: Sha
authors.affiliation: Department of Mathematical Sciences, Michigan Technological University, 1400 Townsend Drive, Houghton, MI 49931, USA.
authors.forename: Shuanglin
authors.initials: S
authors.lastname: Zhang