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Office of Neuroscience Research > Neuroscience Calendar > Division of Biostatistics Seminar: Han Chen (University of Texas Health Science Center at Houston)

Division of Biostatistics Seminar: Han Chen (University of Texas Health Science Center at Houston)

"Efficient Association Tests for Rare Genetic Variants in Correlated Study Samples" 


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When: Friday, November 03, 2017 at 12:30 PM to 1:30 PM
Where: Becker Library 502 (Medical Campus, 5th floor)

Abstract: With the advance in next-generation sequencing technology, massive genetic and genomic data have been produced. These data are often sparse, as most genetic variants in the human genome are rare mutations with very low minor allele frequencies. Statistical methods for testing genetic association with these rare genetic variants have been well established and widely applied to unrelated samples. These methods are also known as gene-based or variant-set tests, since rare variants are often grouped by genes, functional units or genomic regions in the analysis. In recent years, large-scale sequencing projects such as NHLBI’s Trans-Omics for Precision Medicine (TOPMed) program have included study samples from family studies, or with cryptic relatedness, and there is a pressing need of developing efficient statistical methods to analyze these data. Here we propose and implement efficient association tests for rare genetic variants in correlated study samples in the generalized linear mixed model framework. We show in simulation studies that the proposed tests control correct type I error rates in both single-cohort studies and meta-analysis. We compare the power of these tests in various scenarios and illustrate how they can be used to test a broad class of different scientific hypotheses in large-scale sequencing studies. We also apply the methods to a real data example from a large exome sequencing study of Type 2 diabetes.

Coffee, water, and cookies will be provided

Visit the calendar for the full list of Division of Biostatistics seminars.

For inquiries contact Chengjie Xiong.   



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