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使用卡方模型对交叉干扰进行统计分析。

Statistical analysis of crossover interference using the chi-square model.

作者信息

Zhao H, Speed T P, McPeek M S

机构信息

Department of Statistics, University of California, Berkeley 94720, USA.

出版信息

Genetics. 1995 Feb;139(2):1045-56. doi: 10.1093/genetics/139.2.1045.

Abstract

The chi-square model (also known as the gamma model with integer shape parameter) for the occurrence of crossovers along a chromosome was first proposed in the 1940's as a description of interference that was mathematically tractable but without biological basis. Recently, the chi-square model has been reintroduced into the literature from a biological perspective. It arises as a result of certain hypothesized constraints on the resolution of randomly distributed crossover intermediates. In this paper under the assumption of no chromatid interference, the probability for any single spore or tetrad joint recombination pattern is derived under the chi-square model. The method of maximum likelihood is then used to estimate the chi-square parameter m and genetic distances among marker loci. We discuss how to interpret the goodness-of-fit statistics appropriately when there are some recombination classes that have only a small number of observations. Finally, comparisons are made between the chi-square model and some other tractable models in the literature.

摘要

沿染色体发生交叉的卡方模型(也称为形状参数为整数的伽马模型)最早于20世纪40年代提出,用于描述干扰,该模型在数学上易于处理,但没有生物学基础。最近,卡方模型又从生物学角度被重新引入文献。它是对随机分布的交叉中间体分辨率施加某些假设约束的结果。在本文中,在无染色单体干扰的假设下,推导了卡方模型下任何单个孢子或四分体联合重组模式的概率。然后使用最大似然法估计卡方参数m和标记位点之间的遗传距离。我们讨论了在某些重组类别观测值很少时如何恰当地解释拟合优度统计量。最后,对卡方模型与文献中的其他一些易于处理的模型进行了比较。

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