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利用 RFLP 图谱估计存在性状误分类时的无偏重组值。

Estimation of unbiased recombination values in the presence of misclassification of a trait using RFLP maps.

机构信息

Laboratory of Biometrics, Division of Agriculture and Agricultural Life Sciences, The University of Tokyo, Yayoi 1-1-1, Bunkyo, 113, Tokyo, Japan.

出版信息

Theor Appl Genet. 1996 Apr;92(5):524-31. doi: 10.1007/BF00224554.

Abstract

The effect of misclassification of phenotypes of a trait on the estimation of recombination value was investigated. The effect was larger for closer linkage. If a locus is dominant and linked with the misclassfied trait locus in the repulsion phase, then the effect on the recombination value between the two loci is largest. A method for estimating the unbiased recombination value and the misclassification rate using maximum likelihood associated with an EM algorithm is also presented. This method was applied to a numerical example from rice genome data. It was concluded that the present method combined with the metric multi-dimensional scaling method is useful for the detection of misclassified markers and for the estimation of unbiased recombination values.

摘要

研究了表型错分对重组值估计的影响。错分的表型与连锁越紧密,其影响越大。如果一个基因座是显性的,并且在相斥相时与被错分的性状基因座连锁,那么对两个基因座之间的重组值的影响最大。本文还提出了一种利用最大似然法和 EM 算法来估计无偏重组值和错分率的方法。该方法应用于水稻基因组数据的数值实例。结论认为,本方法与度量多维标度法相结合,可用于检测错分标记和估计无偏重组值。

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