With ever-larger sample sizes, the size of the error terms in the SNP effect estimates will be reduced, and the two statistics will converge to the same value. However, simulations for human populations suggest that the improvement in trait prediction as sample size increases depends on the genetic architecture of the trait, in particular how many variants there are with tiny effect sizes, and that for most common complex genetic diseases the improvement will be slow and modest even when common SNPs account for a large proportion of heritability of the traits17. Hence, for applications in human populations to achieve meaningful and accurate predictions, big data are key and sample sizes of hundreds of thousands needed and such data sets are starting to become achievable.
