Counting methods (EM algorithm) in human pedigree analysis: Linkage and segregation analysis

The likelihood of human pedigree data can be written in such a form as to allow the computation of derivatives. This is done for various parameters in linkage and segregation analysis. The equations for the maximum likelihood estimates are represented in a particularly appealing form which allows it...

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Bibliographic Details
Published inAnnals of human genetics Vol. 40; no. 4; pp. 443 - 454
Main Author OTT, JURG
Format Journal Article
LanguageEnglish
Published England 01.05.1977
Subjects
Gene Frequency
Genetic Linkage
Genotype
Humans
Mathematics
Pedigree
Phenotype
Recombination, Genetic
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ISSN0003-4800
1469-1809
DOI10.1111/j.1469-1809.1977.tb02031.x

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Summary:The likelihood of human pedigree data can be written in such a form as to allow the computation of derivatives. This is done for various parameters in linkage and segregation analysis. The equations for the maximum likelihood estimates are represented in a particularly appealing form which allows iterative solutions. This process is an extension to pedigress of Smith's (1957) counting methods. All these procedures belong to a general class of MLE methods for incomplete data called EM algorithms (Dempster et al. 1976).
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ISSN:0003-4800
1469-1809
DOI:10.1111/j.1469-1809.1977.tb02031.x