Simple jQuery Dropdowns
Please use this identifier to cite or link to this item:
Title: Methods for meta-analyses of genome-wide association studies: Critical assessment of empirical evidence
Authors: Martin Gögele
Cosetta Minelli
Ammarin Thakkinstian
Alex Yurkiewich
Cristian Pattaro
Peter P. Pramstaller
Julian Little
John Attia
John R. Thompson
EURAC Research
Mahidol University
University of Ottawa, Canada
University of Newcastle, Australia
University of Leicester
Keywords: Medicine
Issue Date: 15-Apr-2012
Citation: American Journal of Epidemiology. Vol.175, No.8 (2012), 739-749
Abstract: There has been a steep increase in the number of meta-analyses of genome-wide association (GWA) studies aimed at identifying genetic variants with increasingly smaller effects, but pressure to publish findings of new genetic associations has limited the time available for careful consideration of all of their methodological aspects. The authors surveyed the literature (2007-2010) to provide empirical evidence on the methods used in GWA meta-analyses, including their organization, requirements about the uniformity of methods used in primary studies, methods for data pooling, investigation of between-study heterogeneity, and quality of reporting. This review showed that a great variety of methods are being used, but the rationale for their choice is often unclear. It also highlights how important methodological aspects have received insufficient attention, potentially leading to missed opportunities for improving gene discovery and characterization. Evaluation of power to replicate findings was inadequate, and the number of variants selected for replication was not associated with replication sample size. A low proportion of GWA meta-analyses investigated the presence and magnitude of heterogeneity, even when there was little uniformity in methods used in primary studies. More methodological work is required before clear guidance can be offered as to optimal methods or tradeoffs between alternative methods. However, there is a clear need for guidelines for reporting the results of GWA meta-analyses. © The Author 2012. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved.
ISSN: 14766256
Appears in Collections:Scopus 2011-2015

Files in This Item:
There are no files associated with this item.

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.