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Cited by 539

The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.

Quality control and conduct of genome-wide association meta-analyses

Open access
The Genetic Investigation of Anthropometric Traits (GIANT) Consortium, Winkler, Thomas W, Day, Felix R, Croteau-Chonka, Damien C, Wood, Andrew R, Locke, Adam E, Mägi, Reedik, Ferreira, Teresa, Fall, Tove, Graff, Mariaelisa, Justice, Anne E, Luan, Jian'an, Gustafsson, Stefan, Randall, Joshua C, Vedantam, Sailaja, Workalemahu, Tsegaselassie, Kilpeläinen, Tuomas O, Scherag, André, Esko, Tonu, Kutalik, Zoltán, Heid, Iris M, Loos, Ruth J F·2014·Nature Protocols
DOI 10.1038/nprot.2014.071
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Abstract

Rigorous organization and quality control (QC) are necessary to facilitate successful genome-wide association meta-analyses (GWAMAs) of statistics aggregated across multiple genome-wide association studies. This protocol provides guidelines for (i) organizational aspects of GWAMAs, and for (ii) QC at the study file level, the meta-level across studies and the meta-analysis output level. Real-world examples highlight issues experienced and solutions developed by the GIANT Consortium that has conducted meta-analyses including data from 125 studies comprising more than 330,000 individuals. We provide a general protocol for conducting GWAMAs and carrying out QC to minimize errors and to guarantee maximum use of the data. We also include details for the use of a powerful and flexible software package called EasyQC. Precise timings will be greatly influenced by consortium size. For consortia of comparable size to the GIANT Consortium, this protocol takes a minimum of about 10 months to complete.

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Research works printed but not linked: 23

  1. McCarthy, M.I. & Hirschhorn, J.N. Genome-wide association studies: past, present and future. Human Mol. Genet. 17, R100–R101 (2008). · DOI
  2. Hirschhorn, J.N. & Gajdos, Z.K. Genome-wide association studies: results from the first few years and potential implications for clinical medicine. Annu. Rev. Med. 62, 11–24 (2011). · DOI
  3. Randall, J.C. et al. Sex-stratified genome-wide association studies including 270,000 individuals show sexual dimorphism in genetic loci for anthropometric traits. PLoS Genet. 9, e1003500 (2013). · DOI · Paper page
  4. Surakka, I. et al. A genome-wide screen for interactions reveals a new locus on 4p15 modifying the effect of waist-to-hip ratio on total cholesterol. PLoS Genet. 7, e1002333 (2011). · DOI
  5. Manning, A.K. et al. A genome-wide approach accounting for body mass index identifies genetic variants influencing fasting glycemic traits and insulin resistance. Nat. Genet. 44, 659–669 (2012). · DOI · Paper page
  6. Voight, B.F. et al. The metabochip, a custom genotyping array for genetic studies of metabolic, cardiovascular, and anthropometric traits. PLoS Genet. 8, e1002793 (2012). · DOI · Paper page
  7. Huyghe, J.R. et al. Exome array analysis identifies new loci and low-frequency variants influencing insulin processing and secretion. Nat. Genet. 45, 197–201 (2013). · DOI · Paper page
  8. Heid, I.M. et al. Meta-analysis identifies 13 new loci associated with waist-hip ratio and reveals sexual dimorphism in the genetic basis of fat distribution. Nat. Genet. 42, 949–960 (2010). · DOI · Paper page
  9. Speliotes, E.K. et al. Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index. Nat. Genet. 42, 937–948 (2010). · DOI · Paper page
  10. Scott, R.A. et al. Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways. Nat. Genet. 44, 991–1005 (2012). · DOI · Paper page
  11. Schunkert, H. et al. Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease. Nat. Genet. 43, 333–338 (2011). · DOI · Paper page
  12. Willer, C.J. et al. Six new loci associated with body mass index highlight a neuronal influence on body weight regulation. Nat. Genet. 41, 25–34 (2009). · DOI · Paper page
  13. Lindgren, C.M. et al. Genome-wide association scan meta-analysis identifies three loci influencing adiposity and fat distribution. PLoS Genet. 5, e1000508 (2009). · DOI · Paper page
  14. Manning, A.K. et al. Meta-analysis of gene-environment interaction: joint estimation of SNP and SNP × environment regression coefficients. Genet. Epidemiol. 35, 11–18 (2011). · DOI · Paper page
  15. Fuchsberger, C., Taliun, D., Pramstaller, P.P., Pattaro, C. & CKDGen Consortium. GWAtoolbox: an R package for fast quality control and handling of genome-wide association studies meta-analysis data. Bioinformatics 28, 444–445 (2012). · DOI
  16. Kottgen, A. et al. Genome-wide association analyses identify 18 new loci associated with serum urate concentrations. Nat. Genet. 45, 145–154 (2013). · DOI · Paper page
  17. Kottgen, A. et al. New loci associated with kidney function and chronic kidney disease. Nat. Genet. 42, 376–384 (2010). · DOI · Paper page
  18. Schizophrenia Psychiatric Genome-Wide Association Study Consortium. Genome-wide association study identifies five new schizophrenia loci. Nat. Genet. 43, 969–976 (2011). · DOI · Paper page
  19. Knoppers, B.M., Dove, E.S., Litton, J.E. & Nietfeld, J.J. Questioning the limits of genomic privacy. Am. J. Hum. Genet. 91, 577–578: author reply 579 (2012). · DOI
  20. Gymrek, M., McGuire, A.L., Golan, D., Halperin, E. & Erlich, Y. Identifying personal genomes by surname inference. Science 339, 321–324 (2013). · DOI · Paper page
  21. Visscher, P.M. & Hill, W.G. The limits of individual identification from sample allele frequencies: theory and statistical analysis. PLoS Genet. 5, e1000628 (2009). · DOI
  22. Yang, J. et al. Genomic inflation factors under polygenic inheritance. Eur. J. Hum. Genet. 19, 807–812 (2011). · DOI · Paper page
  23. Whitlock, M.C. Combining probability from independent tests: the weighted Z-method is superior to Fisher's approach. J. Evol. Biol. 18, 1368–1373 (2005). · DOI · Paper page

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Metadata

Authors
The Genetic Investigation of Anthropometric Traits (GIANT) Consortium, Winkler, T. W., Day, F. R., Croteau-Chonka, D. C., Wood, A. R., Locke, A. E., Mägi, R., Ferreira, T., Fall, T., Graff, M., Justice, A. E., Luan, J., Gustafsson, S., Randall, J. C., Vedantam, S., Workalemahu, T., Kilpeläinen, T. O., Scherag, A., Esko, T., Kutalik, Z., Heid, I. M., & Loos, R. J. F.
Venue
Nature Protocols
Publisher
Springer Science and Business Media LLC
Published
2014-04-24
Volume
9
Issue
5
Pages
1192-1212
ISSN
  • 1750-2799 (ISSN-L)
  • 1754-2189
DOI
10.1038/nprot.2014.071
OpenAlex
W2115193738
Cited by
539
References
16
FWCI
14.66
Type
journal article
Language
en
Open access
green
Licence
www.springer.com/tdm (tdm)

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CoChat. (2026). Citation check: Quality control and conduct of genome-wide association meta-analyses. https://app.cochat.ai/papers/10.1038/nprot.2014.071
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The Genetic Investigation of Anthropometric Traits (GIANT) Consortium, Winkler, T. W., Day, F. R., Croteau-Chonka, D. C., Wood, A. R., Locke, A. E., Mägi, R., Ferreira, T., Fall, T., Graff, M., Justice, A. E., Luan, J., Gustafsson, S., Randall, J. C., Vedantam, S., Workalemahu, T., Kilpeläinen, T. O., Scherag, A., Esko, T., . . . Loos, R. J. F. (2014). Quality control and conduct of genome-wide association meta-analyses. Nature Protocols. https://doi.org/10.1038/nprot.2014.071

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