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The tree of blobs of a species network: identifiability under the coalescent.
Allman, Elizabeth S; Baños, Hector; Mitchell, Jonathan D; Rhodes, John A.
Afiliação
  • Allman ES; Department of Mathematics and Statistics, University of Alaska Fairbanks, Fairbanks, AK, 99775, USA.
  • Baños H; Department of Biochemistry and Molecular Biology, Faculty of Medicine, Dalhousie University, Halifax, NS, Canada.
  • Mitchell JD; Department of Mathematics and Statistics, Faculty of Science, Dalhousie University, Halifax, NS, Canada.
  • Rhodes JA; Department of Mathematics and Statistics, University of Alaska Fairbanks, Fairbanks, AK, 99775, USA.
J Math Biol ; 86(1): 10, 2022 12 06.
Article em En | MEDLINE | ID: mdl-36472708
Inference of species networks from genomic data under the Network Multispecies Coalescent Model is currently severely limited by heavy computational demands. It also remains unclear how complicated networks can be for consistent inference to be possible. As a step toward inferring a general species network, this work considers its tree of blobs, in which non-cut edges are contracted to nodes, so only tree-like relationships between the taxa are shown. An identifiability theorem, that most features of the unrooted tree of blobs can be determined from the distribution of gene quartet topologies, is established. This depends upon an analysis of gene quartet concordance factors under the model, together with a new combinatorial inference rule. The arguments for this theoretical result suggest a practical algorithm for tree of blobs inference, to be fully developed in a subsequent work.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Genômica Tipo de estudo: Prognostic_studies Idioma: En Revista: J Math Biol Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Alemanha

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Genômica Tipo de estudo: Prognostic_studies Idioma: En Revista: J Math Biol Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Alemanha