“polygenic scores” (PGS), “genetic risk scores” (GRS) and “polygenic risk scores” (PRS) are now used interchangeably to describe metrics comprising a large number of SNPs pooled together to represent a measured set of variants underlying a particular trait or disease. Dudbridge (Dudbridge, 2013) examined the power and predictive accuracy of polygenic scores for discrete and continuous traits and found that large discovery samples, which best separate the true from null effects at the tail of the p-value distribution, yield the most precise polygenic scores. In the post-GWAS era, the use of existing GWAS results, such as those from the Psychiatric Genomics Consortium, can be used as “discovery” samples form which to generate polygenic scores for a novel study. Tools for automated creation of polygenic scores are available in the Plink 2 software package (Chang et al., 2015).
