Methods for meta-analyses of genome-wide association studies: Critical assessment of empirical evidence
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 al...
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th-mahidol.148372018-06-11T12:12:41Z Methods for meta-analyses of genome-wide association studies: Critical assessment of empirical evidence 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 Medicine 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. 2018-06-11T05:12:41Z 2018-06-11T05:12:41Z 2012-04-15 Article American Journal of Epidemiology. Vol.175, No.8 (2012), 739-749 10.1093/aje/kwr385 14766256 00029262 2-s2.0-84859731474 https://repository.li.mahidol.ac.th/handle/123456789/14837 Mahidol University SCOPUS https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84859731474&origin=inward |
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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. |
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EURAC Research |
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EURAC Research Martin Gögele Cosetta Minelli Ammarin Thakkinstian Alex Yurkiewich Cristian Pattaro Peter P. Pramstaller Julian Little John Attia John R. Thompson |
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Article |
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Martin Gögele Cosetta Minelli Ammarin Thakkinstian Alex Yurkiewich Cristian Pattaro Peter P. Pramstaller Julian Little John Attia John R. Thompson |
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Martin Gögele |
title |
Methods for meta-analyses of genome-wide association studies: Critical assessment of empirical evidence |
title_short |
Methods for meta-analyses of genome-wide association studies: Critical assessment of empirical evidence |
title_full |
Methods for meta-analyses of genome-wide association studies: Critical assessment of empirical evidence |
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Methods for meta-analyses of genome-wide association studies: Critical assessment of empirical evidence |
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Methods for meta-analyses of genome-wide association studies: Critical assessment of empirical evidence |
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methods for meta-analyses of genome-wide association studies: critical assessment of empirical evidence |
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2018 |
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https://repository.li.mahidol.ac.th/handle/123456789/14837 |
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1763492010222682112 |