Although individually significant markers in genome-wide association scans (GWAS) explain limited heritability of complex traits, evidence has been accruing that a considerable proportion of phenotypic variation can be explained by the ensemble of markers not achieving significance. Thus, while most of the specific genes underlying complex traits have yet to be identified, it is likely that many are represented on current genotyping products and specific identification is largely a matter of study size [1]. Polygenic score analysis has recently generated much interest for assessing the explanatory power of an ensemble of markers. A GWAS is conducted on an initial training sample, and the markers are ranked by their evidence for association, usually their P-values. An independent replication sample is then analysed by constructing, for each subject, a polygenic score consisting of the weighted sum of its trait-associated alleles, for some subset of top ranking markers. Two related but distinct applications of this score are then possible. Firstly, testing for association between the score and the trait in the replication sample can determine whether associated markers reside within those contributing to
