Nsengimana, J and Bishop, DT orcid.org/0000-0002-8752-8785 (2017) Design Considerations for Genetic Linkage and Association Studies. In: Statistical Human Genetics: Methods and Protocols. Methods in Molecular Biology, 1666 . Humana Press , New York , pp. 257-281. ISBN 9781493972739
Abstract
This chapter describes the main issues that genetic epidemiologists usually consider in the design of linkage and association studies. For linkage, we briefly consider the situation of rare highly penetrant alleles showing a disease pattern consistent with Mendelian inheritance investigated through parametric methods in large pedigrees, or with autozygosity mapping in inbred families, and we then turn our focus to the most common design, the affected sibling pair design that is of more relevance for common, complex diseases. Power and sample size calculations are provided as a function of the strength of the genetic effect being investigated. We also discuss the impact of other determinants of statistical power such as disease heterogeneity, pedigree and genotyping errors and the effect of the type and density of genetic markers. For association studies, we consider the popular case-control design for dichotomous phenotypes and we provide power and sample size calculations for one-stage and multistage designs. For candidate genes, guidelines are given on the prioritization of genetic variants, and for genome-wide association studies (GWAS) the issue of choosing an appropriate SNP array is discussed. A warning is issued regarding the danger of designing an underpowered replication study following an initial GWAS. The risk of finding spurious association due to population stratification, cryptic relatedness, and differential bias is underlined.
Metadata
Item Type: | Book Section |
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Authors/Creators: |
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Keywords: | Association; Cryptic relatedness; Differential bias; False positives; Heterogeneity; Linkage; Marker density; Power; Sib pairs; Stratification |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) > Institute of Molecular Medicine (LIMM) (Leeds) > Section of Epidemiology and Biostatistics (Leeds) |
Funding Information: | Funder Grant number Cancer Research UK c588/A19167 |
Depositing User: | Symplectic Publications |
Date Deposited: | 25 May 2018 15:00 |
Last Modified: | 25 May 2018 15:00 |
Status: | Published |
Publisher: | Humana Press |
Series Name: | Methods in Molecular Biology |
Identification Number: | 10.1007/978-1-4939-7274-6_13 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:131224 |