Multiple Phenotype---Multiple Genotype Testing with Principle Components

• Activity Number: 42 - Statistical Genetics I – New Approaches for Association Mapping
• Type: Contributed
• Date/Time: Monday, August 3, 2020 : 10:00 AM to 2:00 PM
• Sponsor: Section on Statistics in Genomics and Genetics
• Author(s): Andy Shi* and Ryan Sun and Xihong Lin
• Companies: Harvard TH Chan School of Public Health and University of Texas, MD Anderson Cancer Center and Harvard TH Chan School of Public Health
• Keywords: Genome-wide association studies (GWAS); Omnibus test; Principle component analysis; Multiple phenotypes

Abstract

The increasing popularity of large-scale genetic compendiums has driven a recent interest in testing sets of genotypes against a single phenotype and testing sets of phenotypes against a single genotype. Incorporating the information from these correlated sets of variants and outcomes can offer more power to detect novel associations, reduce the multiple testing burden in massive datasets, and produce more interpretable conclusions about the genetic etiology of complex diseases by incorporating prior biological knowledge into set definitions. However, less work has focused on the testing problem when sets are formed for both genotypes and phenotypes. In this paper, we propose and study the performance of principle components-based methods that can jointly test for the association between multiple phenotypes and multiple genotypes. We demonstrate how the operating characteristics of each test are determined by the correlation structures of the genotypes and phenotypes as well as the direction of effects linking the two sets. We also propose an omnibus test that is robust to the direction of the effects. We apply our method to analyze correlated lipid biomarkers in the UK Biobank.