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估计核苷酸替换模式及位点间替换率变化的近似方法。

Approximate methods for estimating the pattern of nucleotide substitution and the variation of substitution rates among sites.

作者信息

Yang Z, Kumar S

机构信息

Institute of Molecular Evolutionary Genetics, Pennsylvania State University, USA.

出版信息

Mol Biol Evol. 1996 May;13(5):650-9. doi: 10.1093/oxfordjournals.molbev.a025625.

Abstract

We propose two approximate methods (one based on parsimony and one on pairwise sequence comparison) for estimating the pattern of nucleotide substitution and a parsimony-based method for estimating the gamma parameter for variable substitution rates among sites. The matrix of substitution rates that represents the substitution pattern can be recovered through its relationship with the observable matrix of site pattern frequences in pairwise sequence comparisons. In the parsimony approach, the ancestral sequences reconstructed by the parsimony algorithm were used, and the two sequences compared are those at the ends of a branch in the phylogenetic tree. The method for estimating the gamma parameter was based on a reinterpretation of the numbers of changes at sites inferred by parsimony. Three data sets were analyzed to examine the utility of the approximate methods compared with the more reliable likelihood methods. The new methods for estimating the substitution pattern were found to produce estimates quite similar to those obtained from the likelihood analyses. The new method for estimating the gamma parameter was effective in reducing the bias in conventional parsimony estimates, although it also overestimated the parameter. The approximate methods are computationally very fast and appear useful for analyzing large data sets, for which use of the likelihood method requires excessive computation.

摘要

我们提出了两种近似方法(一种基于简约法,另一种基于成对序列比较)来估计核苷酸替换模式,以及一种基于简约法的方法来估计位点间可变替换率的伽马参数。表示替换模式的替换率矩阵可通过其与成对序列比较中位点模式频率的可观测矩阵的关系来恢复。在简约法中,使用简约算法重建的祖先序列,并且所比较的两个序列是系统发育树中一个分支末端的序列。估计伽马参数的方法基于对简约法推断的位点变化数量的重新解释。分析了三个数据集,以检验这些近似方法与更可靠的似然法相比的效用。发现用于估计替换模式的新方法产生的估计值与从似然分析中获得的估计值非常相似。用于估计伽马参数的新方法在减少传统简约估计中的偏差方面是有效的,尽管它也高估了该参数。这些近似方法计算速度非常快,对于分析大型数据集似乎很有用,因为使用似然法需要进行过多的计算。

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