用两两序列比较法推断同源性的一个基本限制
A basic limitation on inferring phylogenies by pairwise sequence comparisons
摘要：
遗传学中基于距离的方法，如邻居连接，是一种快速和流行的构建树的方法。这些方法从它们中提取序列对，构建一个值，在预期中，该值在位点替换的随机模型下是可加的。大多数模型假设利率在各个地点之间的分布，通常基于伽马分布。只要已知该分布的形状参数，该方法就能正确地重建树。然而，如果形状参数是未知的，那么我们表明，拓扑结构不同的树，具有不同的形状参数和相关的正分支长度，可以导致完全匹配的分布成对网站模式之间的所有对分类群。因此，在没有形状参数的一些先验知识的情况下，不能使用序列对来区分两棵树。更令人惊讶的是，对于两棵树上的不同形状参数的{ \em any}选择，这可能发生，因此结果不是形状参数的特定或人为选择所特有的。在一个积极的注意，我们指出了已知的条件下，可识别性可以恢复（即，当分支长度是时钟，或者如果使用的方法，如最大似然）。
英文摘要：
Distance-based approaches in phylogenetics such as Neighbor-Joining are a fast and popular approach for building trees. These methods take pairs of sequences from them construct a value that, in expectation, is additive under a stochastic model of site substitution. Most models assume a distribution of rates across sites, often based on a gamma distribution. Provided the (shape) parameter of this distribution is known, the method can correctly reconstruct the tree. However, if the shape parameter is not known then we show that topologically different trees, with different shape parameters and associated positive branch lengths, can lead to exactly matching distributions on pairwise site patterns between all pairs of taxa. Thus, one could not distinguish between the two trees using pairs of sequences without some prior knowledge of the shape parameter. More surprisingly, this can happen for {\em any} choice of distinct shape parameters on the two trees, and thus the result is not peculiar to a particular or contrived selection of the shape parameters. On a positive note, we point out known conditions where identifiability can be restored (namely, when the branch lengths are clocklike, or if methods such as maximum likelihood are used).
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
