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A0259
Title: Enhancing power of rare variant association test by a zoom-focus algorithm to locate optimal testing region Authors:  Maggie Haitian Wang - the Chinese University of Hong Kong (Hong Kong) [presenting]
Abstract: The increasing amount of whole exome or genome sequencing data brings forth the challenge of analyzing the association of rare variants that have extremely small minor allele frequencies. Various statistical tests have been proposed, which are specifically configured to increase power for rare variants by conducting the test within a certain bin, such as a gene or a pathway. However, a gene may contain from several to thousands of markers, and not all of them are related to the phenotype. Combining functional and non-functional variants in arbitrary genomic region could impair the testing power. We propose a Zoom-Focus Algorithm (ZFA) to locate the optimal testing region within a given genomic region. It can be applied as a wrapper function of existing rare variant association tests to increase testing power. The algorithm is very efficient and the complexity is linear to the number of variants. Simulation studies showed that ZFA substantially increased the statistical power of rare variants tests, including the burden test, SKAT, SKAT-O, and the W-test. The algorithm was applied on real exome sequencing data of hypertensive disorder, and identified biologically relevant genetic markers to metabolic disorder that were undiscoverable by gene-based method. The proposed algorithm is an efficient and powerful tool to enhance the power of association study for whole exome or genome sequencing data.