Other recent methodological work on PRSs has been performed primarily in the context of EA populations. Shi et al. (2016) suggested to penalize the estimated effect sizes used in a PRS, by fitting an l1-penalized regression. It is a topic of future work to suggest an approach that reduces the computational burden of applying shrinkage estimation procedure in mixed models and test its utility for improving the effect size estimates in an admixed population training dataset. Vilhjálmsson et al. (2015) proposed LDpred for incorporating information from GWAS summary statistics and a reference panel to use information from multiple SNPs, rather than only the lead SNP, from an association region. While they demonstrated this method to be useful under specific priors for genetic architecture, their approach hinges on having a good reference panel. Different admixed populations differ in their admixture patterns, so the same reference panel may not be appropriate across the board. It will be interesting to study and potentially extend Vilhjálmsson et al. (2015)’s approach to admixed populations, despite the lack of training and testing samples with the same
