Using Gene Genealogies to Localize Rare Variants Associated with Complex Traits in Diploid Populations

Abstract

Background and Aims: Many methods can detect trait association with causal variants in candidate genomic regions; however, a comparison of their ability to localize causal variants is lacking. We extend a previous study of the detection abilities of these methods to a comparison of their localization abilities. Methods: Through coalescent simulation, we compare several popular association methods. Cases and controls are sampled from a diploid population to mimic human studies. As benchmarks for comparison, we include two methods that cluster phenotypes on the true genealogical trees: a naive Mantel test considered previously in haploid populations and an extension that takes into account whether case haplotypes carry a causal variant. We first work through a simulated dataset to illustrate the methods. We then perform a simulation study to score the localization and detection properties. Results: In our simulations, the association signal was localized least precisely by the naive Mantel test and most precisely by its extension. Most other approaches had intermediate performance similar to the single-variant Fisher exact test. Conclusions: Our results confirm earlier findings in haploid populations about potential gains in performance from genealogy-based approaches. They also highlight differences between haploid and diploid populations when localizing and detecting causal variants.