Association analysis of whole genome sequencing data accounting for longitudinal and family designs

BMC Proceedings

Proceedings

Yijuan Hu¹  Qin Hui²  Yan V Sun³ 

[1] Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, USA;Department of Epidemiology, Emory University, Atlanta, GA, USA;Department of Epidemiology, Emory University, Atlanta, GA, USA;Department of Biomedical Informatics, Emory University, Atlanta, GA, USA;Center for Health Research, Kaiser Permanente Georgia, Atlanta, GA, USA;

关键词: Systolic Blood Pressure;    Rare Variant;    Genetic Analysis Workshop;    Unrelated Subject;    Burden Score;   

DOI  :  10.1186/1753-6561-8-S1-S89

来源: Springer

【 摘 要 】

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.

【 授权许可】

Unknown   
© Hu et al.; licensee BioMed Central Ltd. 2014. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.