Our study enables us to make several general recommendations relevant to GWA studies. The first relates to the importance of careful quality control. In such large data sets, small systematic differences can readily produce effects capable of obscuring the true associations being sought111,112. We implemented extensive quality control checks to minimize differences in sample DNA concentration, quality and handling procedures and combined a new genotype-calling algorithm (CHIAMO) with a set of filtering heuristics to select SNPs for further analysis. Given that infallible detection of incorrect genotype calls is not yet possible, the criteria used for SNP exclusion need to strike a compromise between stringency (which may discard true signals or generate spurious positives through differential missingness) and leniency (with the danger that true signals are swamped by spurious findings due to poor genotype calling). As such, systematic visual inspection of cluster plots for SNPs of interest remains an integral part of the quality control process.
