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Adjusting for familial relatedness in the analysis of GWAS data

Thomson, R and McWhirter, R ORCID: 0000-0002-9409-8074 2017 , 'Adjusting for familial relatedness in the analysis of GWAS data', in JM Keith (ed.), Bioinformatics: Volume II: Structure, Function, and Applications. Methods in Molecular Biology , Humana Press, New York, United States, pp. 175-190.

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Abstract

Relatedness within a sample can be of ancient (population stratification) or recent (familial structure) origin, and can either be known (pedigree data) or unknown (cryptic relatedness). All of these forms of familial relatedness have the potential to confound the results of genome-wide association studies. This chapter reviews the major methods available to researchers to adjust for the biases introduced by relatedness and maximize power to detect associations. The advantages and disadvantages of different methods are presented with reference to elements of study design, population characteristics, and computational requirements.

Item Type: Book Section
Authors/Creators:Thomson, R and McWhirter, R
Keywords: genomewide association studies, GWAS, relatedness, confounding, population stratification, cryptic relatedness, familial structure
Publisher: Humana Press
DOI / ID Number: 10.1007/978-1-4939-6613-4_10
Copyright Information:

Copyright 2017 Springer Science+Business Media New York

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