A Method to Exploit the Structure of Genetic Ancestry Space to Enhance Case Control Studies

• Activity Number: 189
• Type: Contributed
• Date/Time: Monday, August 4, 2014 : 10:30 AM to 12:20 PM
• Sponsor: IMS
• Author(s): Corneliu Alexandru Bodea*+ and Bernie Devlin and Kathryn Roeder
• Companies: Carnegie Mellon and University of Pittsburgh School of Medicine and CMU
• Keywords: genetic association studies ; genetic ancestry mapping ; Bayesian spatial prediction ; hierarchical clustering ; Gaussian process model ; spectral clustering

Abstract

In genetic studies of common and rare variants, considerable effort and expense is required to obtain a sample of control subjects matched by genetic ancestry to the case subjects. Our proposed approach, the Universal Control Repository Network (UNICORN), aims to process data from collections like dbGap and provide allele frequency information that is optimally matched to the case sample, which would obviate the need for collecting additional large control samples. To maintain the confidentiality of both cases and controls we will use existing publicly available collections of control data to create a common genetic ancestry space onto which cases and control can be mapped independently via spectral clustering. The base space and projected controls are then used to estimate the allele frequency surface over the ancestry space. To identify smallscale frequency variation while also borrowing strength from the entire data set we employ a combination of empirical Bayesian analysis across a hierarchical clustering of the controls and, for localized ancestry regions, a Gaussian process model of the minor allele frequency.