To overcome these issues, genotyping imputation algorithms were developed. These methods use information provided by high quality markers combined with genome structure information for the population of interest organized in the HapMap database. These procedures can potentially be a nearly zero-cost alternative to increase both power and coverage in individual GWA studies. The imputation procedures allow meta- and pooled analyses of GWAS data generated by distinct genotyping platforms, maximizing their overlap and, consequently, the number of typed individuals. Despite promising, the success of imputation algorithms are relative since they could also amplify non-detected technical errors in genotyped markers, the available HapMap information may not be well consolidated for the population of interest or the applied imputation algorithm may not be well suited for a specific dataset [7].
