Higher criticism approach to detect rare variants using whole genome sequencing data

BMC Proceedings

Proceedings

Li Yang¹  Zheyang Wu¹  Jing Xuan¹ 

[1] Department of Mathematical Science, Worcester Polytechnic Institute, 100 Institute Road, 01609-2280, Worcester, MA, USA;

关键词: Rare Variant;    Whole Genome Sequencing;    Association Test;    Whole Genome Sequencing Data;    High Criticism;   

DOI  :  10.1186/1753-6561-8-S1-S14

来源: Springer

【 摘 要 】

Because of low statistical power of single-variant tests for whole genome sequencing (WGS) data, the association test for variant groups is a key approach for genetic mapping. To address the features of sparse and weak genetic effects to be detected, the higher criticism (HC) approach has been proposed and theoretically has proven optimal for detecting sparse and weak genetic effects. Here we develop a strategy to apply the HC approach to WGS data that contains rare variants as the majority. By using Genetic Analysis Workshop 18 "dose" genetic data with simulated phenotypes, we assess the performance of HC under a variety of strategies for grouping variants and collapsing rare variants. The HC approach is compared with the minimal p-value method and the sequence kernel association test. The results show that the HC approach is preferred for detecting weak genetic effects.

【 授权许可】

Unknown   
© Xuan 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.