Transcriptome-guided imaging genetic analysis via a novel sparse CCA algorithm

Alzheimer’s Disease Neuroimaging Initiative

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

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 be 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.

Original languageEnglish (US)
Title of host publicationGraphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics - 1st International Workshop, GRAIL 2017 6th International Workshop, MFCA 2017 and 3rd International Workshop, MICGen 2017 Held in Conjunction with MICCAI 2017, Proceedings
PublisherSpringer Verlag
Pages220-229
Number of pages10
Volume10551 LNCS
ISBN (Print)9783319676746
DOIs
StatePublished - 2017
Event1st International Workshop on Graphs in Biomedical Image Analysis, GRAIL 2017, 6th International Workshop on Mathematical Foundations of Computational Anatomy, MFCA 2017 and 3rd International Workshop on Imaging Genetics, MICGen 2017 held in Conjunction with 20th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2017 - Quebec City, Canada
Duration: Sep 10 2017Sep 14 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10551 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other1st International Workshop on Graphs in Biomedical Image Analysis, GRAIL 2017, 6th International Workshop on Mathematical Foundations of Computational Anatomy, MFCA 2017 and 3rd International Workshop on Imaging Genetics, MICGen 2017 held in Conjunction with 20th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2017
CountryCanada
CityQuebec City
Period9/10/179/14/17

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Alzheimer’s Disease Neuroimaging Initiative (2017). Transcriptome-guided imaging genetic analysis via a novel sparse CCA algorithm. In Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics - 1st International Workshop, GRAIL 2017 6th International Workshop, MFCA 2017 and 3rd International Workshop, MICGen 2017 Held in Conjunction with MICCAI 2017, Proceedings (Vol. 10551 LNCS, pp. 220-229). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10551 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-67675-3_20