title: Bayesian Generalized Low Rank Regression Models for Neuroimaging Phenotypes and Genetic Markers.
abstract: We propose a Bayesian generalized low rank regression model (GLRR) for the analysis of both high-dimensional responses and covariates. This development is motivated by performing searches for associations between genetic variants and brain imaging phenotypes. GLRR integrates a low rank matrix to approximate the high-dimensional regression coefficient matrix of GLRR and a dynamic factor model to model the high-dimensional covariance matrix of brain imaging phenotypes. Local hypothesis testing is developed to identify significant covariates on high-dimensional responses. Posterior computation proceeds via an efficient Markov chain Monte Carlo algorithm. A simulation study is performed to evaluate the finite sample performance of GLRR and its comparison with several competing approaches. We apply GLRR to investigate the impact of 1,071 SNPs on top 40 genes reported by AlzGene database on the volumes of 93 regions of interest (ROI) obtained from Alzheimer's Disease Neuroimaging Initiative (ADNI).
authors.affiliation: H. Zhu is Professor of Biostatistics ( hzhu@bios.unc.edu ), Z. Khondker was a Ph.d student under the supervision of Drs. Ibrahim and Zhu ( zakaria.khondker@medivation.com ), Z. Lu was a postdoctoral fellow under the supervision of Dr. Zhu ( zhaohua.lu@gmail.com ), and J. G. Ibrahim is Alumni Distinguished Professor of Biostatistics ( ibrahim@bios.unc.edu ), Department of Biostatistics, University of North Carolina at Chapel Hill, NC 27599-7420.
authors.forename: Hongtu
authors.initials: H
authors.lastname: Zhu
authors.affiliation: H. Zhu is Professor of Biostatistics ( hzhu@bios.unc.edu ), Z. Khondker was a Ph.d student under the supervision of Drs. Ibrahim and Zhu ( zakaria.khondker@medivation.com ), Z. Lu was a postdoctoral fellow under the supervision of Dr. Zhu ( zhaohua.lu@gmail.com ), and J. G. Ibrahim is Alumni Distinguished Professor of Biostatistics ( ibrahim@bios.unc.edu ), Department of Biostatistics, University of North Carolina at Chapel Hill, NC 27599-7420.
authors.forename: Zakaria
authors.initials: Z
authors.lastname: Khondker
authors.affiliation: H. Zhu is Professor of Biostatistics ( hzhu@bios.unc.edu ), Z. Khondker was a Ph.d student under the supervision of Drs. Ibrahim and Zhu ( zakaria.khondker@medivation.com ), Z. Lu was a postdoctoral fellow under the supervision of Dr. Zhu ( zhaohua.lu@gmail.com ), and J. G. Ibrahim is Alumni Distinguished Professor of Biostatistics ( ibrahim@bios.unc.edu ), Department of Biostatistics, University of North Carolina at Chapel Hill, NC 27599-7420.
authors.forename: Zhaohua
authors.initials: Z
authors.lastname: Lu
authors.affiliation: H. Zhu is Professor of Biostatistics ( hzhu@bios.unc.edu ), Z. Khondker was a Ph.d student under the supervision of Drs. Ibrahim and Zhu ( zakaria.khondker@medivation.com ), Z. Lu was a postdoctoral fellow under the supervision of Dr. Zhu ( zhaohua.lu@gmail.com ), and J. G. Ibrahim is Alumni Distinguished Professor of Biostatistics ( ibrahim@bios.unc.edu ), Department of Biostatistics, University of North Carolina at Chapel Hill, NC 27599-7420.
authors.forename: Joseph G
authors.initials: JG
authors.lastname: Ibrahim
keywords: Generalized low rank regression; Genetic variant; High dimension; Imaging phenotype; Markov chain Monte Carlo; Penalized method