Comparison of association mapping methods in a complex pedigreed population

Association mapping methods were compared using a simulation with a complex pedigree structure. The pedigree was simulated while keeping the present Danish Holstein population pedigree in view. A total of 15 quantitative trait loci (QTL) with varying effect sizes (10%, 5% and 2% of total genetic variance) were simulated. We compared the single‐marker test, haplotype‐based analysis, mixed model approach, and Bayesian analysis. The methods were compared for power, precision of location estimates, and type I error rates. Results found the best performance in a Bayesian method that included genetic background effects and simultaneously fitted all single‐nucleotide polymorphisms (SNPs) with a variable selection method. A mixed model analysis that fitted genetic background effects and tested one SNP at a time performed nearly as well as the Bayesian method. For the Bayesian method, it proved necessary to collect SNP signals in intervals, to avoid the scattering of a QTL signal over multiple neighboring SNPs. Methods not accounting for genetic background (full pedigree information) performed worse, and methods using haplotypes were considerably worse with a high false‐positive rate, probably due to the presence of low‐frequency haplotypes. It was necessary to account for full relationships among individuals to avoid excess false discovery. Although the methods were tested on a cattle pedigree, the results are applicable to any population with a complex pedigree structure. Genet. Epidemiol. 34: 455–462, 2010. © 2010 Wiley‐Liss, Inc.