Colloquium - Xuexia Wang

Xuexia Wang, Associate Professor, Department of Mathematics, University of North Texas

Title: A General Statistic to Test an Optimally Weighted Combination of Common and/or Rare Variants in Association Studies

Abstract: Both traditional genome-wide association study and next generation sequencing data analysis are widely employed in order to identify disease susceptible common and/or rare genetic variants in many large-scale genetic studies. Generally, rare variants have large effects but are difficult to detect due to their low frequency.  Currently, many existing statistical methods for rare variants association studies have employed a weighted combination scheme, which usually puts subjective weights or suboptimal weights based on some ad hoc assumptions (e.g. ignoring dependence between rare variants). Actually, the independence assumption is inconsistent with results from coalescent models, such an assumption can lead to inflated type I error rate as documented in the literature. In this talk, I will present a new approach without making the independence assumption. I will show the results from simulation studies as well as the results of application to a real data set.


Friday, February 15, 2019 at 1:05 p.m.

Fisher 131

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