遗传关系的贝叶斯区间估计：在亲子鉴定中的应用。
Bayesian interval estimation of genetic relationships: application to paternity testing.
作者信息
Goldgar D E, Thompson E A
机构信息
Department of Preventive Medicine, University of Mississippi School of Medicine, Jackson.
出版信息
Am J Hum Genet. 1988 Jan;42(1):135-42.
Using genetic marker data, we have developed a general methodology for estimating genetic relationships between a set of individuals. The purpose of this paper is to illustrate the practical utility of these methods as applied to the problem of paternity testing. Bayesian methods are used to compute the posterior probability distribution of the genetic relationship parameters. Use of an interval-estimation approach rather than a hypothesis-testing one avoids the problem of the specification of an appropriate null hypothesis in calculating the probability of paternity. Monte Carlo methods are used to evaluate the utility of two sets of genetic markers in obtaining suitably precise estimates of genetic relationship as well as the effect of the prior distribution chosen. Results indicate that with currently available markers a "true" father may be reliably distinguished from any other genetic relationship to the child and that with a reasonable number of markers one can often discriminate between an unrelated individual and one with a second-degree relationship to the child.
利用遗传标记数据，我们开发了一种用于估计一组个体之间遗传关系的通用方法。本文的目的是说明这些方法在亲子鉴定问题中的实际应用。贝叶斯方法用于计算遗传关系参数的后验概率分布。使用区间估计方法而非假设检验方法避免了在计算父权概率时指定适当零假设的问题。蒙特卡罗方法用于评估两组遗传标记在获得适当精确的遗传关系估计方面的效用以及所选先验分布的影响。结果表明，使用目前可用的标记，可以可靠地将“真正的”父亲与孩子的任何其他遗传关系区分开来，并且使用合理数量的标记通常可以区分与孩子无亲缘关系的个体和与孩子有二级亲缘关系的个体。
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