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Algorithms for MDC-Based Multi-locus Phylogeny Inference

机译:基于MDC的多位点系统发育推断算法

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One of the criteria for inferring a species tree from a collection of gene trees, when gene tree incongruence is assumed to be due to incomplete lineage sorting (ILS), is minimize deep coalescence, or MDC. Exact algorithms for inferring the species tree from rooted, binary trees under MDC were recently introduced. Nevertheless, in phylogenetic analyses of biological data sets, estimated gene trees may differ from true gene trees, be incompletely resolved, and not necessarily rooted. In this paper, we propose new MDC formulations for the cases where the gene trees are unrooted/binary, rootedon-binary, and unrootedon-binary. Further, we prove structural theorems that allow us to extend the algorithms for the rooted/binary gene tree case to these cases in a straightforward manner. Finally, we study the performance of these methods in coalescent-based computer simulations.
机译:从基因树集合中推断物种树的标准之一是,假设基因树不一致是由于不完整的谱系排序(ILS)导致的,则应将深度合并或MDC降至最低。最近介绍了在MDC下从有根的二叉树推断物种树的精确算法。但是,在生物学数据集的系统发育分析中,估计的基因树可能与真实的基因树不同,无法完全解析,并且不一定扎根。在本文中,我们针对基因树为无根/二进制,有根/非二进制和无根/非二进制的情况提出了新的MDC公式。此外,我们证明了结构定理,这些结构定理使我们能够以直接的方式将针对根/二进制基因树的算法扩展到这些情况。最后,我们在基于合并的计算机仿真中研究了这些方法的性能。

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