Fused multi-modal similarity network as prior in guiding brain imaging genetic association.

ABSTRACT:

Introduction

Brain imaging genetics aims to explore the genetic architecture underlying brain structure and functions. Recent studies showed that the incorporation of prior knowledge, such as subject diagnosis information and brain regional correlation, can help identify significantly stronger imaging genetic associations. However, sometimes such information may be incomplete or even unavailable.

Methods

In this study, we explore a new data-driven prior knowledge that captures the subject-level similarity by fusing multi-modal similarity networks. It was incorporated into the sparse canonical correlation analysis (SCCA) model, which is aimed to identify a small set of brain imaging and genetic markers that explain the similarity matrix supported by both modalities. It was ap

SUBMITTER: He B 

PROVIDER: S-EPMC10196480 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature