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Overview of Statistical Methods for Genome-Wide Association Studies (GWAS)

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Genome-Wide Association Studies and Genomic Prediction

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1019))

Abstract

This chapter provides an overview of statistical methods for genome-wide association studies (GWAS) in animals, plants, and humans. The simplest form of GWAS, a marker-by-marker analysis, is illustrated with a simple example. The problem of selecting a significance threshold that accounts for the large amount of multiple testing that occurs in GWAS is discussed. Population structure causes false positive associations in GWAS if not accounted for, and methods to deal with this are presented. Methodology for more complex models for GWAS, including haplotype-based approaches, accounting for identical by descent versus identical by state, and fitting all markers simultaneously are described and illustrated with examples.

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Author information

Authors and Affiliations

  1. Biosciences Research Division, Department of Primary Industries, Bundoora, VIC, Australia

    Ben Hayes

  2. La Trobe University, Bundoora, VIC, Australia

    Ben Hayes

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  1. Ben Hayes
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Editor information

Editors and Affiliations

  1. , Ctr. Genetic Analysis and Applications, University of New England, Homestead Building 18, Armidale, 2351, New South Wales, Australia

    Cedric Gondro

  2. School of Environmental and Rural Scienc, Div. Animal Science, University of New England, Homestead Building 36, Armidale, 2351, New South Wales, Australia

    Julius van der Werf

  3. , Biosciences Research Division, Department of Primary Industries, Ring Road 5, Bundoora, 3083, Victoria, Australia

    Ben Hayes

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Hayes, B. (2013). Overview of Statistical Methods for Genome-Wide Association Studies (GWAS). In: Gondro, C., van der Werf, J., Hayes, B. (eds) Genome-Wide Association Studies and Genomic Prediction. Methods in Molecular Biology, vol 1019. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-62703-447-0_6

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  • DOI: https://doi.org/10.1007/978-1-62703-447-0_6

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  • Publisher Name: Humana Press, Totowa, NJ

  • Print ISBN: 978-1-62703-446-3

  • Online ISBN: 978-1-62703-447-0

  • eBook Packages: Springer Protocols

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