The method used here does not estimate the effect of each individual SNP as is the case in (genome-wide) association studies (Manolio 2010) and genetic prediction studies (Wray et al. 2007) – in those methodologies, summing the estimates of SNP effects also sums the error component of those estimates and thus does not yield an unbiased estimate of the variance explained by the aggregate of all SNP effects. Instead, we computed one unbiased estimate of the aggregate effect of all SNPs. Conceptually, this is achieved by determining to what extent genetic similarity (at the SNPs) between all individuals corresponds to their phenotypic similarity. Technically, the SNP effects are treated as random effects in a mixed linear model and the total trait variance explained by all the SNPs is estimated by restricted maximum likelihood (REML) analysis, as implemented in the freely available Genome-wide Complex Trait Analysis (GCTA) program (Yang et al. 2011b; see http://gump.qimr.edu.au/gcta/). Technical details of the method are described in Yang et al (2010) and Yang et al (2011b), and a plainer language explanation of the method and common misunderstandings is provided by Visscher et al (2010).
