Wall Jeffrey D
Program in Molecular and Computational Biology, University of Southern California, Los Angeles, California 90089, USA.
Genetics. 2004 Jul;167(3):1461-73. doi: 10.1534/genetics.103.025742.
We introduce a new method for jointly estimating crossing-over and gene conversion rates using sequence polymorphism data. The method calculates probabilities for subsets of the data consisting of three segregating sites and then forms a composite likelihood by multiplying together the probabilities of many subsets. Simulations show that this new method performs better than previously proposed methods for estimating gene conversion rates, but that all methods require large amounts of data to provide reliable estimates. While existing methods can easily estimate an "average" gene conversion rate over many loci, they cannot reliably estimate gene conversion rates for a single region of the genome.
我们介绍了一种使用序列多态性数据联合估计交叉率和基因转换率的新方法。该方法计算由三个分离位点组成的数据子集的概率，然后通过将许多子集的概率相乘形成复合似然。模拟表明，这种新方法在估计基因转换率方面比先前提出的方法表现更好，但所有方法都需要大量数据才能提供可靠的估计。虽然现有方法可以轻松估计多个位点上的“平均”基因转换率，但它们无法可靠地估计基因组单个区域的基因转换率。
