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Transcriptome-Guided Imaging Genetic Analysis via a Novel Sparse CCA Algorithm.


ABSTRACT: Imaging genetics is an emerging field that studies the influence of genetic variation on brain structure and function. The major task is to examine the association between genetic markers such as single nucleotide polymorphisms (SNPs) and quantitative traits (QTs) extracted from neuroimaging data. Sparse canonical correlation analysis (SCCA) is a bi-multivariate technique used in imaging genetics to identify complex multi-SNP-multi-QT associations. In imaging genetics, genes associated with a phenotype should at least expressed in the phenotypical region. We study the association between the genotype and amyloid imaging data and propose a transcriptome-guided SCCA framework that incorporates the gene expression information into the SCCA criterion. An alternating optimization method is used to solve the formulated problem. Although the problem is not biconcave, a closed-form solution has been found for each subproblem. The results on real data show that using the gene expression data to guide the feature selection facilities the detection of genetic markers that are not only associated with the identified QTs, but also highly expressed there.

SUBMITTER: Liu K 

PROVIDER: S-EPMC6171533 | biostudies-other | 2017

REPOSITORIES: biostudies-other

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Transcriptome-Guided Imaging Genetic Analysis via a Novel Sparse CCA Algorithm.

Liu Kefei K   Yao Xiaohui X   Yan Jingwen J   Chasioti Danai D   Risacher Shannon S   Nho Kwangsik K   Saykin Andrew A   Shen Li L  

Graphs in biomedical image analysis, computational anatomy and imaging genetics : First International Workshop, GRAIL 2017, 6th International Workshop, MFCA 2017, and Third International Workshop, MICGen 2017, held in conjunction with M... 20170908


Imaging genetics is an emerging field that studies the influence of genetic variation on brain structure and function. The major task is to examine the association between genetic markers such as single nucleotide polymorphisms (SNPs) and quantitative traits (QTs) extracted from neuroimaging data. Sparse canonical correlation analysis (SCCA) is a bi-multivariate technique used in imaging genetics to identify complex multi-SNP-multi-QT associations. In imaging genetics, genes associated with a ph  ...[more]

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