Imaging genetics via sparse canonical correlation analysis

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dc.citation.firstpage740
dc.citation.journalTitle2013 IEEE 10th International Symposium on Biomedical Imaging (ISBI)
dc.citation.lastpage743
dc.contributor.authorChi, Eric C.
dc.contributor.authorAllen, Genevera I.
dc.contributor.authorZhou, Hua
dc.contributor.authorKohannim, Omid
dc.contributor.authorLange, Kenneth
dc.contributor.authorThompson, Paul M.
dc.date.accessioned2014-10-08T21:25:35Z
dc.date.available2014-10-08T21:25:35Z
dc.date.issued2013
dc.description.abstractThe collection of brain images from populations of subjects who have been genotyped with genome-wide scans makes it feasible to search for genetic effects on the brain. Even so, multivariate methods are sorely needed that can search both images and the genome for relationships, making use of the correlation structure of both datasets. 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 extend recent work on penalized matrix decomposition to account for the correlations in both datasets. Such methods show promise in imaging genetics as they exploit the natural covariance in the datasets. They also avoid an astronomically heavy statistical correction for searching the whole genome and the entire image for promising associations.
dc.identifier.citationChi, Eric C., Allen, Genevera I., Zhou, Hua, et al.. "Imaging genetics via sparse canonical correlation analysis." <i>2013 IEEE 10th International Symposium on Biomedical Imaging (ISBI),</i> (2013) IEEE: 740-743. http://dx.doi.org/10.1109/ISBI.2013.6556581.
dc.identifier.doihttp://dx.doi.org/10.1109/ISBI.2013.6556581
dc.identifier.urihttps://hdl.handle.net/1911/77452
dc.language.isoeng
dc.publisherIEEE
dc.rightsThis is an author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by IEEE.
dc.subject.keyworddiffusion tensor imaging
dc.subject.keywordgenome wide association
dc.subject.keywordcanonical correlation analysis
dc.subject.keywordsparsity
dc.subject.keywordlasso
dc.titleImaging genetics via sparse canonical correlation analysis
dc.typeJournal article
dc.type.dcmiText
dc.type.publicationpost-print
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