SURFBAT: a surrogate family-based association test building on large imputation reference panels

Abstract

AbstractGenotype-phenotype association tests are typically adjusted for population stratification using principal components that are estimated genome-wide. This lacks resolution when analysing populations with fine structure and/or individuals with fine levels of admixture. This can affect power and precision, and is a particularly relevant consideration when control individuals are recruited using geographic selection criteria. Such is the case in France where we have recently created reference panels of individuals anchored to different geographic regions. To make correct comparisons against case groups, who would likely be gathered from large urban areas, new methods are needed.We present SURFBAT (a SURrogate Family Based Association Test) which performs an approximation of the transmission-disequilibrium test. Our method hinges on the application of genotype imputation algorithms to match similar haplotypes between the case and control groups. This permits us to approximate local ancestry informed posterior probabilities of un-transmitted parental alleles of each case individual. SURFBAT provides an association test that is inherently robust to fine-scale population stratification and opens up the possibility of efficiently using large imputation reference panels as control groups for association testing. The method is suitable when the control panel spans the local ancestry spectrum of the case-group population and each control has similar paternal and maternal ancestries. This is the case for our reference panels where individuals have their four grand-parents born in the same geographic area. In contrast to other methods for association testing that incorporate local-ancestry inference, SURFBAT does not require a set of ancestry groups to be defined, nor for local ancestry to be explicitly estimated.We demonstrate the interest of our tool on simulated datasets created from the 1000 Genomes project and the FranceGenRef project, as well as on a real-data example for a group of case individuals affected by Brugada syndrome.