We also verified that the estimates of variance explained by the SNPs are not driven by a few outlier individuals that are similar in height and in SNP genotypes (Fig. 3). We regressed the squared difference in height between each pair of individuals on the estimate of their relatedness. The intercept and slope are estimates of twice the phenotypic variance and minus twice the additive genetic variance explained by the SNPs, respectively23, so the estimate of variance explained by the SNPs from this regression analysis is ~0.51. The signal on the slope of the regression line comes from many points and is not due to a few outliers. Note that our maximum likelihood estimate is more accurate than this regression analysis; we show the latter only to illustrate the robustness of the estimate. In addition, we performed REML analysis using subsets of individuals by randomly splitting the whole sample into two and four groups and by sampling 1,000, 2,000 and 3,000 individuals with replacement for four replicates (Supplementary Fig. 4). The average estimates of variance explained by all SNPs are not affected by sample size, but, as expected, the sampling error increases as sample size decreases.
