Meta-analysis may be used to improve the power and examine the between-dataset heterogeneity of genome-wide association studies. Prospective designs may be most efficient, if they try to maximize the overlap of genotyping platforms and anticipate the combination of data across many genome-wide association studies.
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Y.F. Ramos, Sarah Metrustry, N K Arden, Anne‐Christine Bay‐Jensen, Marian Beekman, Anton J. M. de Craen, L. Adrienne Cupples, Tõnu Esko, Εvangelos Εvangelou, David T. Felson, Deborah Hart, John P A Ioannidis, M.A. Karsdal, M. Kloppenburg, F.P. Lafeber, Andres Metspalu, Kalliope Panoutsopoulou, P. Eline Slagboom, Tim D. Spector, Erwin W E van Spil, André G. Uitterlinden, Yanyan Zhu,
Εvangelos Εvangelou, Demetrius M. Maraganore, Grazia Annesi, Laura Brighina, Alexis Brice, Alexis Elbaz, Carlo Ferrarese, Georgios M. Hadjigeorgiou, Rejko Krueger, Jean‐Charles Lambert, Suzanne Lesage, Katerina Markopoulou, George D. Mellick, Bram Meeus, Nancy L. Pedersen, Aldo Quattrone, Christine Van Broeckhoven, Manu Sharma, Peter A. Silburn, Eng‐King Tan, Karin Wirdefeldt, John P A Ioannidis
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