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Robust, Universal Tree Balance Indices.
Lemant, Jeanne; Le Sueur, Cécile; Manojlovic, Veselin; Noble, Robert.
Afiliación
  • Lemant J; Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, 4058 Basel, Switzerland.
  • Le Sueur C; Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Kreuzstrasse 2, 4123 Allschwil, Switzerland.
  • Manojlovic V; University of Basel, Petersplatz 1, 4001 Basel, Switzerland.
  • Noble R; Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, 4058 Basel, Switzerland.
Syst Biol ; 71(5): 1210-1224, 2022 08 10.
Article en En | MEDLINE | ID: mdl-35412638
Balance indices that quantify the symmetry of branching events and the compactness of trees are widely used to compare evolutionary processes or tree-generating algorithms. Yet, existing indices are not defined for all rooted trees, are unreliable for comparing trees with different numbers of leaves, and are sensitive to the presence or absence of rare types. The contributions of this article are twofold. First, we define a new class of robust, universal tree balance indices. These indices take a form similar to Colless' index but can account for population sizes, are defined for trees with any degree distribution, and enable meaningful comparison of trees with different numbers of leaves. Second, we show that for bifurcating and all other full m-ary cladograms (in which every internal node has the same out-degree), one such Colless-like index is equivalent to the normalized reciprocal of Sackin's index. Hence, we both unify and generalize the two most popular existing tree balance indices. Our indices are intrinsically normalized and can be computed in linear time. We conclude that these more widely applicable indices have the potential to supersede those in current use. [Cancer; clone tree; Colless index; Sackin index; species tree; tree balance.].
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Algoritmos / Evolución Biológica Tipo de estudio: Prognostic_studies Idioma: En Revista: Syst Biol Asunto de la revista: BIOLOGIA Año: 2022 Tipo del documento: Article País de afiliación: Suiza

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Algoritmos / Evolución Biológica Tipo de estudio: Prognostic_studies Idioma: En Revista: Syst Biol Asunto de la revista: BIOLOGIA Año: 2022 Tipo del documento: Article País de afiliación: Suiza