Here we investigate the use of sparse canonical correlation analysis (CCA) to home in on sets of genetic variants that explain variance in a set of images. We�...
Here we investigate the use of sparse canonical correlation analysis (CCA) to home in on sets of genetic variants that explain variance in a set of images. We�...
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ABSTRACT. The collection of brain images from populations of subjects who have been genotyped with genome-wide scans makes it feasible to search for genetic�...
Sparse canonical correlation analysis (SCCA) is a bi-multivariate analysis method that has the potential to reveal complex multi-SNP-multi-QT associations. Most�...
Here we investigate the use of sparse canonical correlation analysis (CCA) to home in on sets of genetic variants that explain variance in a set of images. We�...
Here we investigate the use of sparse canonical correlation analysis (CCA) to home in on sets of genetic variants that explain variance in a set of images. We�...
Abstract. Motivation: Structured sparse canonical correlation analysis (SCCA) models have been used to identify imaging genetic associations.
Mar 14, 2017 � We propose an analytical framework, based on three-way sparse canonical correlation analysis (T-SCCA), to explore the intrinsic associations among genetic�...
The structured sparse canonical correlation analysis (SCCA) model has been widely used to identify the association between brain image data and genetic data in�...
Sparse canonical correlation analysis (SCCA) is a bi-multivariate technique used in imaging genetics to identify complex multi-SNP-multi-QT associations.