There are several ways to combine datasets in a meta-analysis framework (Figure 2). Meta-analyses can combine p-values or effect sizes. P-value meta-analysis methods have a long history of applications in the social sciences [7], but they became unpopular and had been practically abandoned in the biomedical sciences, until some investigators started using them again in the GWA era. Limitations of p-value meta-analyses (difficulties in interpretation of the combined estimate, inability to provide effect sizes, difficulties in addressing heterogeneity, differences in p-values obtained with parametric and non-parametric methods, handling of p-values with p>0.5, among others) have been recognized for decades, and our recommendation is that effect sizes should be combined whenever the data are available, even if there is still debate about the ability of meta-analysis of GWA to yield summary effect sizes that can be readily differentiated in magnitude among themselves (see below).
