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新的启发式方法用于联合物种界定和种系发生树推断。

New heuristic methods for joint species delimitation and species tree inference.

机构信息

Department of Ecology & EvolutionaryBiology, University of Tennessee, 569 Dabney Hall, Knoxville, TN 37996-1610, USA.

出版信息

Syst Biol. 2010 Jan;59(1):59-73. doi: 10.1093/sysbio/syp077. Epub 2009 Nov 10.

Abstract

Species delimitation and species tree inference are difficult problems in cases of recent divergence, especially when different loci have different histories. This paper quantifies the difficulty of jointly finding the division of samples to species and estimating a species tree without constraining the possible assignments a priori. It introduces a parametric and a nonparametric method, including new heuristic search strategies, to do this delimitation and tree inference using individual gene trees as input. The new methods were evaluated using thousands of simulations and 4 empirical data sets. These analyses suggest that the new methods, especially the nonparametric one, may provide useful insights for systematists working at the species level with molecular data. However, they still often return incorrect results.

摘要

物种划分和种系推断是近期分化情况下的难题,尤其是当不同基因座具有不同历史时。本文量化了在没有先验约束可能分配的情况下,共同找到样本物种划分和估计物种树的困难程度。它引入了参数和非参数方法,包括新的启发式搜索策略,使用个体基因树作为输入进行这种划分和树推断。新方法使用数千次模拟和 4 个经验数据集进行了评估。这些分析表明,新方法,特别是非参数方法,可能为使用分子数据在物种水平上工作的系统发育学家提供有用的见解。然而,它们仍然经常返回不正确的结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e510/5841455/8108cdf497e2/sysbiosyp077f01_ht.jpg

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