However, there are also several practical advantages to meta-analysis. For example, in meta-analysis the association testing of a particular study is more likely to be done by an analyst who is quite familiar with the genotype and phenotype data from that study. It may be computationally more feasible to analyze studies separately rather than as single cohorts of >100,000 samples, and the distribution of effort across multiple investigative groups may also ease the computational burden. Finally, it is more appropriate to analyze studies separately if there is heterogeneity in their ascertainment, ancestry, phenotyping, etc. Such heterogeneity is almost always present when the constituent studies have been designed independently in the past. Thus, meta-analysis would still be preferred even if all the individual data became centrally available.
