Booth, David and Heard, Robert and Stewart, Graeme and Goris, An and Dobosi, Rita and Dubois, Bénédicte and Oturai, Annette and Søndergaard, Helle Bach and Sellebjerg, Finn and Saarela, Janna and Leppä, Virpi and Palotie, Aarno and Peltonen, Leena and Fontaine, Bertrand and Cournu-Rebeix, Isabelle and Clerget-Darpoux, Françoise and Babron, Marie-Claude and Weber, Frank and Holsboer, Florian and Müller-Myhsok, Bertram and Rieckmann, Peter and Kroner, Antje and Graham, Colin and Vandenbroeck, Koen and Hawkins, Stanley and D'Alfonso, Sandra and Bergamaschi, Laura and Naldi, Paola and Guerini, Franca R. and Salvetti, Marco and Galimberti, Daniela and Hintzen, Rogier Q. and Duijn, Cornelia van and Lorentzen, Åslaug R. and Celius, Elisabeth Gulowsen and Harbo, Hanne Flinstad and Spurkland, Anne and Cucca, Francesco and Marrosu, Maria Giovanna and Comabella, Manuel and Montalbán, Xavier and Villoslada, Paolo and Olsson, Tomas and Kockum, Ingrid and Hillert, Jan and Ban, Maria and Walton, Amie and Sawcer, Stephen and Compston, Alastair and Hawkins, Clive and Mihalova, Tania and Robertson, Neil P. and Ingram, Gillian and De Jager, Philip L. and Hafler, David A. and Rioux, John D. and Daly, Mark and Barcellos, Lisa F. and Ivinson, Adrian and Pericak-Vance, Margaret and Hoksenberg, Jorge and Hauser, Stephen and McCauley, Jacob and Sexton, David and Haines, Jonathan (2008) Refining genetic associations in multiple sclerosis. The Lancet Neurology, Vol. 7 (7), p. 567-569. ISSN 1474-4422. Article.
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Genome-wide association studies involve several hundred thousand markers and, even when quality control is scrupulous, are invariably confounded by residual uncorrected errors that can falsely inflate the apparent difference between cases and controls (so-called genomic inflation). As a consequence such studies inevitably generate false positives alongside genuine associations. By use of Bayesian logic and empirical data, the Wellcome Trust Case Control Consortium suggested that association studies in complex disease should involve at least 2000 cases and 2000 controls, at which level they predicted that p values of less than 5×10−7 would more commonly signify true positives than false positives.
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