Correspondence between fMRI and SNP data by group sparse canonical correlation analysis.

ABSTRACT: Both genetic variants and brain region abnormalities are recognized as important factors for complex diseases (e.g., schizophrenia). In this paper, we investigated the correspondence between single nucleotide polymorphism (SNP) and brain activity measured by functional magnetic resonance imaging (fMRI) to understand how genetic variation influences the brain activity. A group sparse canonical correlation analysis method (group sparse CCA) was developed to explore the correlation between these two datasets which are high dimensional-the number of SNPs/voxels is far greater than the number of samples. Different from the existing sparse CCA methods (sCCA), our approach can exploit structural information in the correlation analysis by introducing group constraints. A simulation study demonstra

SUBMITTER: Lin D 

PROVIDER: S-EPMC4007390 | biostudies-literature | 2014 Aug

REPOSITORIES: biostudies-literature