GN-SCCA: Graphnet based sparse canonical correlation analysis for brain imaging genetics

Lei Du, Jingwen Yan, Sungeun Kim, Shannon L. Risacher, Heng Huang, Mark Inlow, Jason H. Moore, Andrew J. Saykin, Li Shen, Disease Neuroimaging Initiative Alzheimer’s Disease Neuroimaging Initiative

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Identifying associations between genetic variants and neuroimaging quantitative traits (QTs) is a popular research topic in brain imaging genetics. Sparse canonical correlation analysis (SCCA) has been widely used to reveal complex multi-SNP-multi-QT associations. Several SCCA methods explicitly incorporate prior knowledge into the model and intend to uncover the hidden structure informed by the prior knowledge. We propose a novel structured SCCA method using Graph constrained Elastic-Net (GraphNet) regularizer to not only discover important associations, but also induce smoothness between coefficients that are adjacent in the graph. In addition, the proposed method incorporates the covariance structure information usually ignored by most SCCA methods. Experiments on simulated and real imaging genetic data show that, the proposed method not only outperforms a widely used SCCA method but also yields an easy-to-interpret biological findings.

Original languageEnglish (US)
Title of host publicationBrain Informatics and Health - 8th International Conference, BIH 2015, Proceedings
EditorsYike Guo Y., Sean Hill S., Karl Friston, Hanchuan Peng, Aldo Faisal A.
PublisherSpringer Verlag
Pages275-284
Number of pages10
ISBN (Print)9783319233437
DOIs
StatePublished - Jan 1 2015
Event8th International Conference on Brain Informatics and Health, BIH 2015 - London, United Kingdom
Duration: Aug 30 2015Sep 2 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9250
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other8th International Conference on Brain Informatics and Health, BIH 2015
CountryUnited Kingdom
CityLondon
Period8/30/159/2/15

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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    Du, L., Yan, J., Kim, S., Risacher, S. L., Huang, H., Inlow, M., Moore, J. H., Saykin, A. J., Shen, L., & Alzheimer’s Disease Neuroimaging Initiative, D. N. I. (2015). GN-SCCA: Graphnet based sparse canonical correlation analysis for brain imaging genetics. In Y. Guo Y., S. Hill S., K. Friston, H. Peng, & A. Faisal A. (Eds.), Brain Informatics and Health - 8th International Conference, BIH 2015, Proceedings (pp. 275-284). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9250). Springer Verlag. https://doi.org/10.1007/978-3-319-23344-4_27