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Bayesian interval estimation of genetic relationships: application to paternity testing.

机译:遗传关系的贝叶斯区间估计:在亲子鉴定中的应用。

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摘要

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.
机译:利用遗传标记数据,我们已经开发出一种通用的方法来估算一组个体之间的遗传关系。本文的目的是说明这些方法在亲子鉴定问题上的实际应用。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不是假设检验方法,可以避免在计算亲子关系概率时指定适当的无效假设的问题。蒙特卡洛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以及所选先验分布的影响方面的效用。结果表明,使用当前可用的标记,可以将“真正的”父亲与与该孩子的任何其他遗传关系可靠地区分开,并且使用合理数量的标记,通常可以区分无关的人和与该孩子具有二级关系的人。儿童。

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