Quantifying the accuracy of ancestral state prediction in a phylogenetic tree under maximum parsimony
Quantifying the accuracy of ancestral state prediction in a phylogenetic tree under maximum parsimony
复制标题
量化最大简约下系统发育树中祖先状态预测的准确性
DOI:
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发表时间:
2018
影响因子:
1.9
通讯作者:
M. Steel
中科院分区:
文献类型:
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作者:
Lina Herbst;Heyang Li;M. Steel
In phylogenetic studies, biologists often wish to estimate the ancestral discrete character state at an interior vertex v of an evolutionary tree T from the states that are observed at the leaves of the tree. A simple and fast estimation method—maximum parsimony—takes the ancestral state at v to be any state that minimises the number of state changes in T required to explain its evolution on T. In this paper, we investigate the reconstruction accuracy of this estimation method further, under a simple symmetric model of state change, and obtain a number of new results, both for 2-state characters, and r-state characters (r>2documentclass[12pt]{minimal} usepackage{amsmath} usepackage{wasysym} usepackage{amsfonts} usepackage{amssymb} usepackage{amsbsy} usepackage{mathrsfs} usepackage{upgreek} setlength{oddsidemargin}{-69pt} egin{document}$$r>2$$end{document}). Our results rely on establishing new identities and inequalities, based on a coupling argument that involves a simpler ‘coin toss’ approach to ancestral state reconstruction.
影响因子:
3.3
作者:
Ziheng Yang;Sudhir Kumar;M. Nei
通讯作者:
Ziheng Yang;Sudhir Kumar;M. Nei