eCite Digital Repository

Adjusting for Familial Relatedness in the Analysis of GWAS Data


Thomson, R and McWhirter, R, Adjusting for Familial Relatedness in the Analysis of GWAS Data, Methods in Molecular Biology: Bioinformatics - Volume II: Structure, Function, and Applications., Humana Press, JM Keith (ed), New York, United States, pp. 175-190. ISBN 978-1-4939-6613-4 (2017) [Research Book Chapter]

Copyright Statement

Copyright 2017 Springer Science+Business Media New York

DOI: doi:10.1007/978-1-4939-6613-4_10


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 Details

Item Type:Research Book Chapter
Keywords:genomewide association studies, GWAS, relatedness, confounding, population stratification, cryptic relatedness, familial structure
Research Division:Biological Sciences
Research Group:Genetics
Research Field:Gene mapping
Objective Division:Expanding Knowledge
Objective Group:Expanding knowledge
Objective Field:Expanding knowledge in the health sciences
UTAS Author:McWhirter, R (Dr Rebekah McWhirter)
ID Code:116357
Year Published:2017
Deposited By:Menzies Institute for Medical Research
Deposited On:2017-05-08
Last Modified:2018-06-01

Repository Staff Only: item control page