FPLS-DC: functional partial least squares through distance covariance for imaging genetics.

ABSTRACT:

Motivation

Imaging genetics integrates imaging and genetic techniques to examine how genetic variations influence the function and structure of organs like the brain or heart, providing insights into their impact on behavior and disease phenotypes. The use of organ-wide imaging endophenotypes has increasingly been used to identify potential genes associated with complex disorders. However, analyzing organ-wide imaging data alongside genetic data presents two significant challenges: high dimensionality and complex relationships. To address these challenges, we propose a novel, nonlinear inference framework designed to partially mitigate these issues.

Results

We propose a functional partial least squares through distance covariance (FPLS-DC) framework for efficient genome wide

SUBMITTER: Pan W 

PROVIDER: S-EPMC11034987 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature