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Identifying Circular Orders for Blobs in Phylogenetic Networks

Adv Appl Math(2025)

University of Alaska -Fairbanks Department of Mathematics and Statistics | California State University Department of Mathematics | University of Wisconsin -Madison Department of Statistics | University of Wisconsin -Madison Department of Botany

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Abstract
Interest in the inference of evolutionary networks relating species orpopulations has grown with the increasing recognition of the importance ofhybridization, gene flow and admixture, and the availability of large-scalegenomic data. However, what network features may be validly inferred fromvarious data types under different models remains poorly understood. Previouswork has largely focused on level-1 networks, in which reticulation events arewell separated, and on a general network's tree of blobs, the tree obtained bycontracting every blob to a node. An open question is the identifiability ofthe topology of a blob of unknown level. We consider the identifiability of thecircular order in which subnetworks attach to a blob, first proving that thisorder is well-defined for outer-labeled planar blobs. For this class of blobs,we show that the circular order information from 4-taxon subnetworks identifiesthe full circular order of the blob. Similarly, the circular order from 3-taxonrooted subnetworks identifies the full circular order of a rooted blob. We thenshow that subnetwork circular information is identifiable from certain datatypes and evolutionary models. This provides a general positive result forhigh-level networks, on the identifiability of the ordering in which taxonblocks attach to blobs in outer-labeled planar networks. Finally, we giveexamples of blobs with different internal structures which cannot bedistinguished under many models and data types.
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Semidirected network,Admixture graph,Outer-labeled planar,Quartet,Coalescent,Hybridization
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要点】:该论文探讨了如何识别未知级别的生物进化网络中的环形顺序,创新性地证明了通过4-taxon子网络可以确定blob的完整环形顺序,并通过3-taxon根子网络可以确定根blob的完整环形顺序。

方法】:通过外标记平面blob的环形顺序定义和3-taxon及4-taxon子网络的数据类型,研究了不同模型下网络特征的可识别性。

实验】:论文使用特定数据类型和进化模型,展示了子网络的环形信息是可以识别的,并通过具体例子说明了许多模型和数据类型下blob内部结构无法区分的现象。