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Haplotype Association Analysis

  • Michael P. EpsteinEmail author
  • Lydia C. Kwee
Chapter

Abstract

Haplotypes serve many useful roles in the design and implementation of genetic studies of complex traits. In this chapter, we focus on the use of haplotypes as variables of interest for detecting association between a genomic region and a complex trait. Such haplotype analyses are appealing because, in certain instances, they can be more powerful for association mapping compared to traditionalmethods based on the analysis of individual SNPs. At the same time, haplotype analyses are more complicated to implement than single-SNP analyses since the sample genetic data often consist of unphased genotypes (which often lead to haplotype ambiguity). However, statisticians have developed many innovative methods for haplotype analysis that accommodate such haplotype ambiguity using existing missing-data algorithms. In this section, we describe a variety of such statistical methods for haplotype mapping, which are applicable to genetic datasets collected under traditional population-based and family-based study designs. We further describe software packages that are publicly available for implementing these haplotype approaches. Finally, we illustrate many of these statistical methods and related software packages using unphased genotype data from the Finland-United States Investigation of NIDDM Genetics (FUSION) study.

Keywords

Haplotype Analysis Haplotype Pair Haplotype Effect Environment Interaction Effect Haplotype Cluster 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Notes

Acknowledgements

We thank the FUSION study investigators for allowing us to present results from the analysis of FUSION data. We also thank Dr. Glen Satten for his comments on a previous version of this chapter. This work was supported by National Institutes of Health grants HG003618 and GM074909.

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© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  1. 1.Department of Human GeneticsEmory University School of MedicineAtlantaUSA
  2. 2.Department of BiostatisticsEmory UniversityAtlantaUSA

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