Abstract
Multivariate meta-analysis of genetic association studies and genome-wide association studies has received a remarkable attention as it improves the precision of the analysis. Here, we review, summarize and present in a unified framework methods for multivariate meta-analysis of genetic association studies and genome-wide association studies. Starting with the statistical methods used for robust analysis and genetic model selection, we present in brief univariate methods for meta-analysis and we then scrutinize multivariate methodologies. Multivariate models of meta-analysis for a single gene-disease association studies, including models for haplotype association studies, multiple linked polymorphisms and multiple outcomes are discussed. The popular Mendelian randomization approach and special cases of meta-analysis addressing issues such as the assumption of the mode of inheritance, deviation from Hardy–Weinberg Equilibrium and gene-environment interactions are also presented. All available methods are enriched with practical applications and methodologies that could be developed in the future are discussed. Links for all available software implementing multivariate meta-analysis methods are also provided.
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Acknowledgments
Niki Dimou and Katerina Pantavou were supported by a scholarship from the ΙΚΥ Scholarship Programs in the context of the action “Strengthening Post-Doctoral Research” of the Human Resources Development Program, Education and Lifelong Learning, co-financed by the European Social Fund – ESF and the Greek government.
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Dimou, N.L., Pantavou, K.G., Braliou, G.G., Bagos, P.G. (2018). Multivariate Methods for Meta-Analysis of Genetic Association Studies. In: Evangelou, E. (eds) Genetic Epidemiology. Methods in Molecular Biology, vol 1793. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7868-7_11
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DOI: https://doi.org/10.1007/978-1-4939-7868-7_11
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