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PhySIC: a veto supertree method with desirable properties.

Vincent Ranwez1, Vincent Berry, Alexis Criscuolo

  • 1Institut des Sciences de l'Evolution (ISEM, UMR 5554 CNRS), Université Montpellier II, Montpellier, Cedex 5, France. ranwez@isem.univ-montp2.fr

Systematic Biology
|October 6, 2007
PubMed
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This study introduces the PhySIC method for creating conservative phylogenetic supertrees. PhySIC ensures non-contradiction and induction properties, summarizing evolutionary relationships and identifying data conflicts for consolidation.

Area of Science:

  • Phylogenetics
  • Computational Biology
  • Bioinformatics

Background:

  • Supertree methods aim to synthesize evolutionary relationships from multiple source trees.
  • Veto supertree methods prioritize conservative consensus, avoiding conflicting information.
  • Existing methods may lack clear properties for ensuring topological integrity.

Purpose of the Study:

  • To propose and define desirable properties for veto supertree methods: non-contradiction (PC) and induction (PI).
  • To introduce the PhySIC method for constructing supertrees that satisfy these properties.
  • To provide a tool for summarizing consensual phylogenetic information and highlighting areas needing data consolidation.

Main Methods:

  • Definition of non-contradiction property (PC): supertree must not contradict source topologies.

Related Experiment Videos

  • Definition of induction property (PI): supertree information must be present in or induced by source trees.
  • Introduction of the PhySIC algorithm with a specified time complexity of O(kn(3) + n(4)).

    • Main Results:

    • PC and PI properties can be checked in polynomial time.
    • PhySIC generates supertrees satisfying PC and PI, tagging polytomies with conflict and overlap information.
    • Demonstration of PhySIC on primate datasets, producing a supertree for 95% of extant genera.

    Conclusions:

    • PhySIC offers a robust method for conservative phylogenetic synthesis.
    • The method effectively summarizes consensual data and pinpoints areas of phylogenetic uncertainty.
    • PhySIC provides a valuable tool for evolutionary biologists working with multiple phylogenetic datasets.