Abstract
As genome-wide association studies (GWAS) studies move from array-based genotyping to whole exome and genome sequencing, there is a significant increase in cost. Applying an appropriate technique for the selection of which controls to include, in large studies where more potential controls are available than needed for the study, may be a useful technique for minimizing resource intensity whilst maintaining statistical power. We evaluated three control selection strategies in prostate cancer GWAS using 15 250 UK Biobank cases: (a) all controls, (b) matched controls, and (c) random selection. Both (b) and (c) achieved comparable power in detecting significant loci relative to (a), but matched controls (b) showed greater consistency in identifying leading single nucleotide polymorphisms (SNPs). However, using (b) matched controls reduced discovery power by ~30% compared with (a) all controls, highlighting a trade-off. Matching controls (1:4 ratio) offers a cost-effective approach for targeted SNP analysis across phenotypes but may miss novel associations.