Adjusting for familial relatedness in the analysis of GWAS data

Russell Thomson, Rebekah McWhirter

Research output: Chapter in Book / Conference PaperChapter

6 Citations (Scopus)

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.
Original languageEnglish
Title of host publicationBioinformatics. Volume II: Structure, Function, and Applications
EditorsJonathan M. Keith
Place of PublicationU.S.
PublisherSpringer
Pages175-190
Number of pages16
Edition2nd
ISBN (Electronic)9781493966134
ISBN (Print)9781493966110
DOIs
Publication statusPublished - 2017

Keywords

  • genome-wide association study
  • genomes
  • variation

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