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Computation of Mendelian Likelihoods

  • Kenneth Lange
Part of the Statistics for Biology and Health book series (SBH)

Abstract

Rigorous analysis of human pedigree data is a vital concern in genetic epidemiology, human gene mapping, and genetic counseling. In this chapter we investigate efficient algorithms for likelihood computation on pedigree data, placing particular stress on the pioneering algorithm of Elston and Stewart [5]. It is no accident that their research coincided with the introduction of modern computing. To analyze human pedigree data is tedious, if not impossible, without computers. Pedigrees lack symmetry, and all simple closed-form solutions in mathematics depend on symmetry. The achievement of Elston and Stewart [5] was to recognize that closed-form solutions are less relevant than good algorithms. However, the Elston-Stewart algorithm is not the end of the story. Evaluation of pedigree likelihoods remains a subject sorely in need of further theoretical improvement. Linkage calculations alone are among the most demanding computational tasks in modern biology.

Keywords

Myotonic Dystrophy Recombination Fraction Heterozygous Locus Location Score Exclusion Probability 
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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Copyright information

© Springer Science+Business Media New York 1997

Authors and Affiliations

  • Kenneth Lange
    • 1
  1. 1.Department of Biostatistics and MathematicsUniversity of MichiganAnn ArborUSA

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