estimated from SNPs. The estimate of genetic variance using SNP data in unrelated individuals is free of confounding from common environment effects shared between close relatives that are difficult to model in family-based analyses, and is directly comparable to results from GWAS, because both are based on the same experimental design. For multiple trait analysis, the SNP-based approach allows the estimation of the genetic correlation between complex traits measured on different samples [6], [7]_ENREF_8. This is important in particular for estimating the genetic correlation between diseases because multiple diseases are unlikely to co-segregate in sufficiently large pedigrees to allow estimation using traditional pedigree design. The SNP-based method has the flexibility of estimating the genetic correlation between any two diseases using completely independent case-control data. Other methods to estimate genetic parameters from individual-level or summary GWAS data have also been reported [8]–[10].
