Coal-Miner: a coalescent-based method for GWA studies of quantitative traits with complex evolutionary origins

Association mapping (AM) methods are used in genome-wide association (GWA) studies to test for statistically signi€cant associations between genotypic and phenotypic data. Œe genotypic and phenotypic data share common evolutionary origins – namely, the evolutionary history of sampled organisms – introducing covariance which must be distinguished from the covariance due to biological function that is of primary interest in GWA studies. A variety of methods have been introduced to perform AM while accounting for sample relatedness. However, the state of the art predominantly utilizes the simplifying assumption that sample relatedness is effectively €xed across the genome. In contrast, population genetic theory and empirical studies have shown that sample relatedness can vary greatly across di‚erent loci within a genome; this phenomena – referred to as local genealogical variation – is commonly encountered in many genomic datasets. New AM methods are needed to beŠer account for local variation in sample relatedness within genomes. We address this gap by introducing Coal-Miner, a new statistical AM method. Œe Coal-Miner algorithm takes the form of a methodological pipeline. Œe initial stages of Coal-Miner seek to detect candidate loci, or loci which contain putatively causal markers. Subsequent stages of Coal-Miner perform test for association using a linear mixed model with multiple e‚ects which account for sample relatedness locally within candidate loci and globally across the entire genome. Using synthetic and empirical datasets, we compare the statistical power and type I error control of Coal-Miner against state-of-theart AM methods. Œe simulation conditions reƒect a variety of ∗To whom correspondence should be addressed. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for pro€t or commercial advantage and that copies bear this notice and the full citation on the €rst page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s).