多位点连锁分析的序贯填补法
Sequential imputation for multilocus linkage analysis.
作者信息
Irwin M, Cox N, Kong A
机构信息
Department of Statistics, Ohio State University, Columbus 43210-1247.
出版信息
Proc Natl Acad Sci U S A. 1994 Nov 22;91(24):11684-8. doi: 10.1073/pnas.91.24.11684.
Abstract
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.
摘要
提出了一种名为序贯插补的蒙特卡罗方法用于多位点似然计算。该方法在图谱绘制情况下最为有用，此时数据由带有大量缺失信息的大型家系组成，并且希望同时利用来自多个多态性标记的数据进行连锁分析。一个包含155个个体、9个基因座和155,520个单倍型的家系实例用于说明。
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本文引用的文献
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