Another practical consideration arises when integrating data from studies that use diverse genotyping platforms. Superficially, it is tempting to first impute missing genotypes in each sample and to then conduct a pooled analysis of all available data. However, this is almost never a good idea, as illustrated by a particularly extreme case where a set of cases and controls have been genotyped on two different platforms and a marker of interest has been genotyped in cases but must be imputed in controls. If the marker of interest cannot be well predicted by flanking markers, imputation will default to suggesting that the genotype distribution at that marker matches the reference panel—but this could be a very poor assumption if the reference panel and study sample have drifted apart, potentially resulting in spurious association. Even if the marker can be well predicted by flanking markers, it is possible that the reference panel and the case sample used different genotyping assays that, for technical reasons such as the presence of a polymorphism that overlaps assay primers, give consistently distinct results—again resulting in spurious
