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Activity Number: 33 - Cutting-Edge Statistical Methods for Modeling Disease Progression Processes
Type: Contributed
Date/Time: Sunday, July 30, 2017 : 2:00 PM to 3:50 PM
Sponsor: International Chinese Statistical Association
Abstract #322822
Title: A Powerful Rare-Variant Association Test
Author(s): Zhongxue Chen* and Tong Lin and Kai Wang
Companies: and Peking University and University of Iowa
Keywords: chi-square distribution ; gene-set analysis ; principal component analysis

Detecting the association between a set of rare variants and a given phenotype has attracted a large amount of attention in the scientific community, although it is a difficult task. Recently, many related statistical approaches have been proposed in the literature; powerful statistical tests are still highly desired and yet to be developed in this area. In this paper, we propose a powerful test, which combines information from each individual single nucleotide polymorphisms (SNPs) based on principal component analysis but does not depend on the eigenvalues associated with the principal components. We compare the proposed approach with some popular tests through a simulation study. Our results show that in general the new test is more powerful; the gain in detecting power can be substantial in many situations.

Authors who are presenting talks have a * after their name.

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