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Review
. 2012 May;40(9):3777-84.
doi: 10.1093/nar/gkr1255. Epub 2012 Jan 12.

Comprehensive literature review and statistical considerations for GWAS meta-analysis

Ferdouse Begum  1 , Debashis Ghosh, George C Tseng, Eleanor Feingold
Affiliations
Review

Comprehensive literature review and statistical considerations for GWAS meta-analysis

Ferdouse Begum et al. Nucleic Acids Res. 2012 May.

Abstract

Over the last decade, genome-wide association studies (GWAS) have become the standard tool for gene discovery in human disease research. While debate continues about how to get the most out of these studies and on occasion about how much value these studies really provide, it is clear that many of the strongest results have come from large-scale mega-consortia and/or meta-analyses that combine data from up to dozens of studies and tens of thousands of subjects. While such analyses are becoming more and more common, statistical methods have lagged somewhat behind. There are good meta-analysis methods available, but even when they are carefully and optimally applied there remain some unresolved statistical issues. This article systematically reviews the GWAS meta-analysis literature, highlighting methodology and software options and reviewing methods that have been used in real studies. We illustrate differences among methods using a case study. We also discuss some of the unresolved issues and potential future directions.

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Figures

Figure 1.
Figure 1.
Number of GWAS studies by year of publication. Command used in PubMed search: [‘meta-analysis’(Title/Abstract)] AND [‘genome-wide association’(Title/Abstract)].
Figure 2.
Figure 2.
Summary of GWAS meta-analysis review: (A) type of meta-analysis; (B) type of paper; (C) type of meta-analysis method; (D) software used.
Figure 3.
Figure 3.
Forest plot of the selected SNPs.
See this image and copyright information in PMC

Comment on

References

    1. Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ. 2003;327:557–560. - PMC - PubMed
    1. Ioannidis JP. Non-replication and inconsistency in the genome-wide association setting. Hum. Heredity. 2007;64:203–213. - PubMed
    1. Thompson JR, Attia J, Minelli C. The meta-analysis of genome-wide association studies. Brief. Bioinformatics. 2011;12:259–269. - PubMed
    1. Thompson SG. Why sources of heterogeneity in meta-analysis should be investigated. BMJ. 1994;309:1351–1355. - PMC - PubMed
    1. Guerra R, Goldstein DR. Meta-analysis and Combining Information in Genetics and Genomics. Florence, KY: CRC press, Taylor and Francis Group and a Chapman and Hall book; 2010.

Publication types