Comparing Heritability Estimators under Alternative Structures of Linkage Disequilibrium

Abstract

SNP heritability of a trait is the proportion of its variance explained by the additive effects of the genome-wide single nucleotide polymorphisms (SNPs). The existing approaches to estimate SNP heritability can be broadly classified into two categories. One set of approaches model the SNP effects as fixed effects and the other treats the SNP effects as random effects. These methods make certain assumptions about the dependency among individuals (familial relationship) as well as the dependency among markers (linkage disequilibrium, LD) to provide consistent estimates of SNP heritability as the number of individuals increases. While various approaches have been proposed to account for such dependencies, it remains unclear which estimates reported in the literature are more robust against various model mis-specifications. Here we investigate the impact of different structures of LD and familial relatedness on heritability estimation. We show that the performance of different methods for heritability estimation depends heavily on the structure of the underlying pattern of LD and the degree of relatedness among sampled individuals. However, contrary to the claim in the current literature, we did not find significant differences in the performance of these fixed-SNP-effects and random-SNP-effects approaches. Moreover, we established the equivalence between the two method-of-moments estimators, one from each of these two lines of approaches.