distinct cohorts selected to avoid population stratification, a very common source of bias in GWAS. Imputation algorithms currently available can use very distinct statistical approaches and, overall, their accuracy is satisfactory [3]. Details on the most recent methods, as well as their advantages and limitations, are reviewed and critically discussed elsewhere [9]. Our focus, in this report, is to describe how inferences based on imputed genotypes might impact the discovery of genetic markers possibly associated with complex phenotypes. The results presented here highlight the potential benefits and limitations of the use of imputed data in GWAS association studies for common phenotypes.
