Griffiths R C, Marjoram P
Mathematics Department, Monash University, Clayton, Australia.
J Comput Biol. 1996 Winter;3(4):479-502. doi: 10.1089/cmb.1996.3.479.
The sampling distribution of a collection of DNA sequences is studied under a model where recombination can occur in the ancestry of the sequences. The infinitely-many-sites model of mutation is assumed where there may only be one mutation at a given site. Ancestral inference procedures are discussed for: estimating recombination and mutation rates; estimating the times to the most recent common ancestors along the sequences; estimating ages of mutations; and estimating the number of recombination events in the ancestry of the sample. Inferences are made conditional on the configuration of the pattern of mutations at sites in observed sample sequences. A computational algorithm based on a Markov chain simulation is developed, implemented, and illustrated with examples for these inference procedures. This algorithm is very computationally intensive.
在一个模型下研究了一组DNA序列的抽样分布,该模型中序列的祖先可能发生重组。假设采用无限多位点突变模型,即给定位点可能只发生一次突变。讨论了祖先推断程序,用于:估计重组率和突变率;估计沿序列到最近共同祖先的时间;估计突变年龄;以及估计样本祖先中重组事件的数量。推断是基于观察到的样本序列中位点处突变模式的配置进行的。开发、实现了一种基于马尔可夫链模拟的计算算法,并通过这些推断程序的示例进行了说明。该算法计算量非常大。