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无树根 STAR 方法从基因分裂推断种系树。

Species Tree Inference from Gene Splits by Unrooted STAR Methods.

出版信息

IEEE/ACM Trans Comput Biol Bioinform. 2018 Jan-Feb;15(1):337-342. doi: 10.1109/TCBB.2016.2604812. Epub 2016 Aug 31.

DOI:10.1109/TCBB.2016.2604812
PMID:28113601
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5388605/
Abstract

The method was proposed by Liu and Yu to infer a species tree topology from unrooted topological gene trees. While its statistical consistency under the multispecies coalescent model was established only for a four-taxon tree, simulations demonstrated its good performance on gene trees inferred from sequences for many taxa. Here, we prove the statistical consistency of the method for an arbitrarily large species tree. Our approach connects to a generalization of the STAR method of Liu, Pearl, and Edwards, and a previous theoretical analysis of it. We further show utilizes only the distribution of splits in the gene trees, and not their individual topologies. Finally, we discuss how multiple samples per taxon per gene should be handled for statistical consistency.

摘要

该方法由刘和于提出,用于从无根拓扑基因树推断物种树拓扑结构。虽然在多物种合并模型下,该方法的统计一致性仅在四分类树中得到了证明,但模拟结果表明,该方法在推断许多分类单元的序列基因树时表现良好。在这里,我们证明了该方法在任意大的物种树上的统计一致性。我们的方法与刘、珍珠和爱德华兹的 STAR 方法的推广以及之前对其的理论分析有关。我们进一步表明,该方法仅利用基因树中的分支分布,而不利用它们的个体拓扑结构。最后,我们讨论了如何处理每个基因每个分类单元的多个样本以达到统计一致性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca72/5388605/7e994157b220/nihms854129f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca72/5388605/7e994157b220/nihms854129f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca72/5388605/7e994157b220/nihms854129f1.jpg

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On the Robustness to Gene Tree Estimation Error (or lack thereof) of Coalescent-Based Species Tree Methods.
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PLoS One. 2021 May 10;16(5):e0251107. doi: 10.1371/journal.pone.0251107. eCollection 2021.
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