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[基因库的群体间多样性:赖特F(ST)统计量的贝塔分布]

[Interpopulation diversity of the gene pool: beta distribution of Wright's F(ST) statistics].

作者信息

Nurbaev S D, Balanovskaia E V

机构信息

Institute of Clinical Genetics, Medical Genetic Research Center, Russian Academy of Sciences, Moscow, Russia.

出版信息

Genetika. 1998 Jul;34(7):1004-8.

PMID:9749343
Abstract

The distribution of FST(i) estimates were studied in representative samples of ith genes for the gene pools of the major human populations, including the populations of Europe, Asia, Africa, Australia, America, North-eastern Eurasia, and five subregions of the latter. An average of 80 FST(i) estimates were analyzed for each sample of marker genes with a level of polymorphism (q) from 0.05 to 0.95. For each gene pool, the empirical distributions of FST(i) estimates were approximated by the main types of theoretical distributions--the normal, chi 2, Weibull, gamma, and beta distributions. In all gene pools, only beta distributions were good approximations of the empirical FST(i) distributions. The parameters of the beta distributions are reported in this study. It was demonstrated that the characteristics of beta distributions for all major gene pools studied could be interpolated to the smaller constituent gene pools. since the use of the traditional parametric tests starts from an assumption of normal distribution, they are inapplicable to analysis of FST statistics. Therefore, the obtained parameters of beta distributions should be used. These parameters allow the confidence intervals of the average FST values to be determined and permit correct comparison between the characteristics of both individual genes and gene pools to be performed.

摘要

研究了主要人类群体基因库中第i个基因代表性样本的FST(i)估计值分布,包括欧洲、亚洲、非洲、澳大利亚、美洲、欧亚大陆东北部人群以及后者的五个次区域人群。对每个多态性水平(q)从0.05到0.95的标记基因样本,平均分析了80个FST(i)估计值。对于每个基因库,FST(i)估计值的经验分布由主要类型的理论分布——正态分布、卡方分布、威布尔分布、伽马分布和贝塔分布近似。在所有基因库中,只有贝塔分布能很好地近似FST(i)的经验分布。本研究报告了贝塔分布的参数。结果表明,所研究的所有主要基因库的贝塔分布特征可以内插到较小的组成基因库中。由于传统参数检验的使用始于正态分布假设,它们不适用于FST统计分析。因此,应使用所获得的贝塔分布参数。这些参数可以确定平均FST值的置信区间,并允许对单个基因和基因库的特征进行正确比较。

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