Sequential imputation for multilocus linkage analysis.
A Monte Carlo method called sequential imputation is proposed for multilocus likelihood computations. This method is most useful in mapping situations where the data consist of large pedigrees with substantial missing information and it is desirable to perform linkage analysis utilizing data from many polymorphic markers simultaneously. A pedigree example with 155 individuals, 9 loci, and 155,520 haplotypes is used for illustration.
Department of Statistics, Ohio State University, Columbus 43210-1247.
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M
Irwin
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N
Cox
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A
Kong
D003924:Diabetes Mellitus, Type 2 / Q000235:genetics; D005260:Female; D008040:Genetic Linkage; D006801:Humans; D016013:Likelihood Functions; D008297:Male; D009010:Monte Carlo Method; D010375:Pedigree