Identifying diagnosis-specific genotype-phenotype associations via joint multitask sparse canonical correlation analysis and classification

Lei Du, Fang Liu, Kefei Liu, Xiaohui Yao, Shannon L. Risacher, Junwei Han, Lei Guo, Andrew J. Saykin, Li Shen

Abstract: Brain imaging genetics studies the complex associations between genotypic data such as single nucleotide polymorphisms (SNPs) and imaging quantitative traits (QTs). The neurodegenerative disorders usually exhibit the diversity and heterogeneity, originating from which different diagnostic groups might carry distinct imaging QTs, SNPs and their interactions. Sparse canonical correlation analysis (SCCA) is widely used to identify bi-multivariate genotype–phenotype associations. However, most existing SCCA methods are unsupervised, leading to an inability to identify diagnosis-specific genotype–phenotype associations.