Methods for Meta‐Analysis of Genetic Data
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- Abstract
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- Literature Cited
Abstract
Modern genetic association studies, using genome?wide genotype data, are often underpowered. Meta?analyses of multiple studies performing genome?wide genotyping improve power and have led to the identification of thousands of genotype?trait associations. This unit provides an overview of the key concepts required for genetic meta?analyses, and presents strategic approaches and key decisions that must be made in the process of performing genome?wide association study (GWAS) meta?analyses. The commentary discusses the interpretation of GWAS meta?analysis results, complications, and some of the possible next steps once a GWAS meta?analysis has successfully identified regions associated with a trait. Curr. Protoc. Hum. Genet. 77:1.24.1?1.24.8. © 2013 by John Wiley & Sons, Inc.
Keywords: genome?wide association; GWAS; genetic association analysis; meta?analysis; common variants
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- Introduction
- Key Concepts
- Discussion
- Literature Cited
- Figures
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PDF or HTML at Wiley Online LibraryMaterials
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Figure 1.24.1 Example quantile‐quantile (Q‐Q) plots of ‐log10( p values) for GWAS. (A ) No true effects, and no test statistic inflation. (B ) No true effects, and minor test statistic inflation. (C ) True signal and no test statistic inflation. (D ) No true effects, and stronger test statistic inflation. (E ) True signal and mild test statistic inflation. (F ) Strong true signal and no test statistic inflation. View Image
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Literature Cited
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