Academic Report of School of Mathematical Sciences [2026] No. 108

(Series Report for High-Level University Construction No. 1367)

Title：A Powerful Transformation of Quantitative Responses for Biobank-Scale Association Studies

Speaker：Professor Liu Yaowu (Southwestern University of Finance and Economics)

Time：16:00-17:00, Nov. 5, 2026

Location：Room 611, Huiyan Building

Abstract:In linear regression models with non-Gaussian errors, transformations of the response variable are widely used in a broad range of applications. Motivated by various genetic association studies, transformation methods for hypothesis testing have received substantial interest. In recent years, the rise of biobank-scale genetic studies, which feature a vast number of participants that could be around half a million, spurred the need for new transformation methods that are both powerful for detecting weak genetic signals and computationally efficient for large-scale data. In this work, we propose a novel transformation method that leverages the information of the error density. This transformation leads to locally most powerful tests and therefore has strong power for detecting weak signals. To make the computation scalable to biobank-scale studies, we harnessed the nature of weak genetic signals and proposed a consistent and computationally efficient estimator of the transformation function. Through extensive simulations and a gene-based analysis of spirometry traits from the UK Biobank, we validate that our approach maintains stringent control over Type I error rates and significantly enhances statistical power over existing methods.

Speaker Profile：Liu Yaowu is a professor in the School of Statistics at Southwest University of Finance and Economics. His research interests include large-scale hypothesis testing, statistical genetics, and big data analysis in healthcare. His work has been published in leading statistics and genetics journals such as the JASA, JRSSB, and the American Journal of Human Genetics; in particular, his seminal work on integrated p-values has been cited more than 1,000 times on Google Scholar.

Faculty and students are welcome to attend!

Invited by: Zhou Yan

School of Mathematical Sciences

November 2, 2026