Data Synthesis and Tool Development for Exploring Imaging Genomic Patterns

Abstract

Recent advances in brain imaging and high throughput genotyping techniques enable new approaches to study the influence of genetic variation on brain structure and function. However, major computational challenges are bottlenecks for comprehensive joint analysis of these high-dimensional image and genomic data. We report our initial progress in developing an imaging genomic browsing system for integrated exploration of neuroimaging and genomic data. We describe a method for synthesizing a set of realistic neuroimaging and genomic data, where the relationships between imaging phenotypes and genotypes are known. This data set is used to demonstrate the functionality of our system, which is designed for effectively exploring the neuroanatomical distribution of statistical results that measure the associations between brain imaging phenotypes and genotypes on a genome-wide scale. The proposed system has substantial potential for enabling discovery of important imaging genomic associations through visual evaluation and can be extended towards several directions.