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Statistical Analysis of GWAS

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Phenotypes and Genotypes

Part of the book series: Computational Biology ((COBO,volume 18))

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Abstract

This chapter discusses the statistical analysis of genome-wide association studies. After briefly alluding to the topics of genotype calling and imputation of missing data, we will be mainly concerned with downstream analysis of association, where the genotypes of each individual at each SNP have been established. The classical approach of single marker tests combined with multiple testing correction is contrasted with different strategies of model selection, which tend to perform much better in terms of correctly identifying causal SNPs in the case of complex traits. Specific methods of handling rare SNPs, as well as population stratification, are discussed. The analysis of admixture mapping and gene–gene interactions are amongst the more advanced topics also considered here.

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Authors and Affiliations

  1. Center for Medical Statistics, Informatics, and Intelligent Systems Section for Medical Statistics, Medical University of Vienna, Spitalgasse 23, 1090, Vienna, Austria

    Florian Frommlet

  2. Institute of Mathematics, University of Wrocław, Wrocław, Poland

    Małgorzata Bogdan

  3. Department of Operations Research, Wrocław University of Technology, Wrocław, Poland

    David Ramsey

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  1. Florian Frommlet
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  2. Małgorzata Bogdan
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  3. David Ramsey
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Correspondence to Florian Frommlet .

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Frommlet, F., Bogdan, M., Ramsey, D. (2016). Statistical Analysis of GWAS. In: Phenotypes and Genotypes. Computational Biology, vol 18. Springer, London. https://doi.org/10.1007/978-1-4471-5310-8_5

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