title: HASE: Framework for efficient high-dimensional association analyses.
abstract: High-throughput technology can now provide rich information on a person's biological makeup and environmental surroundings. Important discoveries have been made by relating these data to various health outcomes in fields such as genomics, proteomics, and medical imaging. However, cross-investigations between several high-throughput technologies remain impractical due to demanding computational requirements (hundreds of years of computing resources) and unsuitability for collaborative settings (terabytes of data to share). Here we introduce the HASE framework that overcomes both of these issues. Our approach dramatically reduces computational time from years to only hours and also requires several gigabytes to be exchanged between collaborators. We implemented a novel meta-analytical method that yields identical power as pooled analyses without the need of sharing individual participant data. The efficiency of the framework is illustrated by associating 9 million genetic variants with 1.5 million brain imaging voxels in three cohorts (total N = 4,034) followed by meta-analysis, on a standard computational infrastructure. These experiments indicate that HASE facilitates high-dimensional association studies enabling large multicenter association studies for future discoveries.
authors: Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, Netherlands.|Department of Medical Informatics, Erasmus MC, Rotterdam, Netherlands.
authors: G V
authors: GV
authors: Roshchupkin
authors: Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, Netherlands.|Department of Epidemiology, Erasmus MC, Netherlands.
authors: H H H
authors: HH
authors: Adams
authors: Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, Netherlands.|Department of Epidemiology, Erasmus MC, Netherlands.
authors: M W
authors: MW
authors: Vernooij
authors: Department of Epidemiology, Erasmus MC, Netherlands.
authors: A
authors: A
authors: Hofman
authors: Department of Epidemiology, Erasmus MC, Netherlands.
authors: C M
authors: CM
authors: Van Duijn
authors: Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, Netherlands.|Department of Epidemiology, Erasmus MC, Netherlands.|Department of Neurology, Erasmus MC, Rotterdam, Netherlands.
authors: M A
authors: MA
authors: Ikram
authors: Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, Netherlands.|Department of Medical Informatics, Erasmus MC, Rotterdam, Netherlands.|Faculty of Applied Sciences, Delft University of Technology, Delft, Netherlands.
authors: W J
authors: WJ
authors: Niessen