Academy of Mathematics and Systems Science, CAS
Colloquia & Seminars

Speaker:	李创，中山大学数学学院
Inviter:
Title:	FPLS-DC: Functional partial least squares through distance covariance for imaging genetics
Language:	Chinese
Time & Venue:	2023.05.31 10:00-11:00 思源楼S315
Abstract:	In this work, we propose a functional partial least square through distance covariance (FPLS-DC) framework for efficient whole-genome wide analyses of imaging phenotypes. It consists of two components: The first component utilizes the FPLS-derived base function to reduce image dimensionality while screening genetic markers. The second component maximizes the distance covariance between genetic markers and projected imaging data. We efficiently approximate the null distribution using a gamma approximation. Compared to existing methods, FPLS-DC offers computational and statistical efficiency for handling large-scale imaging genetics. In real-world applications, our approach successfully identifies novel Alzheimer’s disease-related genetic variants and regions of interest, demonstrating its value as a statistical toolbox for imaging genetic studies.