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Haplotype Sharing Methods

  1. Lars Beckmann

Published Online: 15 SEP 2010

DOI: 10.1002/9780470015902.a0022496



How to Cite

Beckmann, L. 2010. Haplotype Sharing Methods. eLS. .

Author Information

  1. German Cancer Research Center, Heidelberg, Germany

Publication History

  1. Published Online: 15 SEP 2010


A convenient way to incorporate haplotypes into statistical analysis of complex diseases is the use of haplotype sharing measures. Statistical methods summarise evolutionary events such as mutation, recombination and coalescence into simple scores to improve the power of association tests. Existing methods provide flexible tools for various study designs such as pedigree data and case-control data, in candidate gene analysis and for genome-wide association analysis. Although haplotype sharing methods were powerful in detecting disease mutations in isolated populations, their applicability for complex diseases in general population deserves further investigation as their potential for possible extensions using a variety of genomic variants, such as copy number variation and uncommon sequence mutations.

Key Concepts:

  • Statistical methods for haplotype sharing analysis in candidate gene association analysis and genome-wide studies have been developed that incorporate information of local haplotypes to improve the power to identify disease susceptibility variants.

  • Haplotype sharing analysis of complex disease relies on population genetic assumptions and incorporates in a convenient way of mutations and recombinations.

  • Statistical methods based on haplotype sharing are available for various study designs, types of trait variable and genetic and nongenetic data.

  • Haplotype sharing analysis extends the identical by descent concept, successfully applied in linkage analysis, to population-based association studies.

  • Reducing a potentially large number of haplotypes to simple similarity scores may reduce degrees of freedom for hypothesis testing, and thus may improve the power.

  • Haplotypes with low frequencies can easily be considered.

  • Haplotype sharing analysis may be more powerful than conventional methods in detecting rare variants.


  • haplotype similarity;
  • haplotype cluster;
  • haplotype scores;
  • haplotype association;
  • nonparametric linkage;
  • isolated populations