title: DATA SYNTHESIS AND METHOD EVALUATION FOR BRAIN IMAGING GENETICS.
abstract: Brain imaging genetics is an emergent research field where the association between genetic variations such as single nucleotide polymorphisms (SNPs) and neuroimaging quantitative traits (QTs) is evaluated. Sparse canonical correlation analysis (SCCA) is a bi-multivariate analysis method that has the potential to reveal complex multi-SNP-multi-QT associations. We present initial efforts on evaluating a few SCCA methods for brain imaging genetics. This includes a data synthesis method to create realistic imaging genetics data with known SNP-QT associations, application of three SCCA algorithms to the synthetic data, and comparative study of their performances. Our empirical results suggest, approximating covariance structure using an identity or diagonal matrix, an approach used in these SCCA algorithms, could limit the SCCA capability in identifying the underlying imaging genetics associations. An interesting future direction is to develop enhanced SCCA methods that effectively take into account the covariance structures in the imaging genetics data.
authors.affiliation: Radiology and Imaging Sciences, BioHealth Informatics, Indiana University, IN, USA.
authors.forename: Jinhua
authors.initials: J
authors.lastname: Sheng
authors.affiliation: Radiology and Imaging Sciences, BioHealth Informatics, Indiana University, IN, USA.
authors.forename: Sungeun
authors.initials: S
authors.lastname: Kim
authors.affiliation: Radiology and Imaging Sciences, BioHealth Informatics, Indiana University, IN, USA.
authors.forename: Jingwen
authors.initials: J
authors.lastname: Yan
authors.affiliation: Genetics, Community and Family Medicine, School of Medicine at Dartmouth College, NH, USA.
authors.forename: Jason
authors.initials: J
authors.lastname: Moore
authors.affiliation: Radiology and Imaging Sciences, BioHealth Informatics, Indiana University, IN, USA.
authors.forename: Andrew
authors.initials: A
authors.lastname: Saykin
authors.affiliation: Radiology and Imaging Sciences, BioHealth Informatics, Indiana University, IN, USA.
authors.forename: Li
authors.initials: L
authors.lastname: Shen
keywords: Sparse canonical correlation analysis; data synthesis; genetics; neuroimaging