Detecting genetic associations with brain imaging phenotypes in Alzheimer's disease via a novel structured SCCA approach.

ABSTRACT: Brain imaging genetics becomes an important research topic since it can reveal complex associations between genetic factors and the structures or functions of the human brain. Sparse canonical correlation analysis (SCCA) is a popular bi-multivariate association identification method. To mine the complex genetic basis of brain imaging phenotypes, there arise many SCCA methods with a variety of norms for incorporating different structures of interest. They often use the group lasso penalty, the fused lasso or the graph/network guided fused lasso ones. However, the group lasso methods have limited capability because of the incomplete or unavailable prior knowledge in real applications. The fused lasso and graph/network guided methods are sensitive to the sign of the sample correlation which m

SUBMITTER: Du L 

PROVIDER: S-EPMC7099577 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature