Several pieces of information are required before embarking on a meta-analysis of GWA datasets (Table 1). Eventually, for each dataset, summary association statistics for each variant and phenotype of interest are generated from the individual-level information. This is done either locally at each participating team or centrally by the coordinating meta-analysis team, if individual-level data are shared. The ability to reproduce the analyses both locally and centrally offers an additional safeguard against errors and inconsistencies or even simple misunderstandings about some aspects of the data. However, such double analysis is often not possible if individual-level data have not been shared. The derived summary statistics may be odds ratios, standardized effect sizes, or other metrics along with their uncertainty (e.g. variance or 95% confidence interval) and/or the accompanying p-values. However, for each dataset, there are also many other items of information that are crucial to deal with. These include:
