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Association analysis of whole genome sequencing data accounting for longitudinal and family designs
Yijuan Hu1, Qin Hui2, Yan V Sun3
1Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, USA.
Abstract:
Using the whole genome sequencing data and the simulated longitudinal phenotypes for 849 pedigree-based individuals from Genetic Analysis Workshop 18, we investigated various approaches to detecting the association of rare and common variants with blood pressure traits. We compared three strategies for longitudinal data: (a) using the baseline measurement only, (b) using the average from multiple visits, and (c) using all individual measurements. We also compared the power of using all of the pedigree-based data and the unrelated subset. The analyses were performed without knowledge of the underlying simulating model.
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