Chapter title |
Design Considerations for Genetic Linkage and Association Studies
|
---|---|
Chapter number | 13 |
Book title |
Statistical Human Genetics
|
Published in |
Methods in molecular biology, January 2017
|
DOI | 10.1007/978-1-4939-7274-6_13 |
Pubmed ID | |
Book ISBNs |
978-1-4939-7273-9, 978-1-4939-7274-6
|
Authors |
Jérémie Nsengimana, D. Timothy Bishop |
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. |
Mendeley readers
Geographical breakdown
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Unknown | 19 | 100% |
Demographic breakdown
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Student > Ph. D. Student | 6 | 32% |
Professor | 3 | 16% |
Researcher | 3 | 16% |
Student > Master | 3 | 16% |
Student > Doctoral Student | 1 | 5% |
Other | 0 | 0% |
Unknown | 3 | 16% |
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Computer Science | 2 | 11% |
Social Sciences | 1 | 5% |
Medicine and Dentistry | 1 | 5% |
Other | 0 | 0% |
Unknown | 5 | 26% |