Literature DB >> 34963003

Robust Analysis of Phylogenetic Tree Space.

Martin R Smith1.   

Abstract

Phylogenetic analyses often produce large numbers of trees. Mapping trees' distribution in "tree space" can illuminate the behavior and performance of search strategies, reveal distinct clusters of optimal trees, and expose differences between different data sources or phylogenetic methods-but the high-dimensional spaces defined by metric distances are necessarily distorted when represented in fewer dimensions. Here, I explore the consequences of this transformation in phylogenetic search results from 128 morphological data sets, using stratigraphic congruence-a complementary aspect of tree similarity-to evaluate the utility of low-dimensional mappings. I find that phylogenetic similarities between cladograms are most accurately depicted in tree spaces derived from information-theoretic tree distances or the quartet distance. Robinson-Foulds tree spaces exhibit prominent distortions and often fail to group trees according to phylogenetic similarity, whereas the strong influence of tree shape on the Kendall-Colijn distance makes its tree space unsuitable for many purposes. Distances mapped into two or even three dimensions often display little correspondence with true distances, which can lead to profound misrepresentation of clustering structure. Without explicit testing, one cannot be confident that a tree space mapping faithfully represents the true distribution of trees, nor that visually evident structure is valid. My recommendations for tree space validation and visualization are implemented in a new graphical user interface in the "TreeDist" R package. [Multidimensional scaling; phylogenetic software; tree distance metrics; treespace projections.].
© The Author(s) 2021. Published by Oxford University Press on behalf of the Society of Systematic Biologists.

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Year:  2022        PMID: 34963003      PMCID: PMC9366458          DOI: 10.1093/sysbio/syab100

Source DB:  PubMed          Journal:  Syst Biol        ISSN: 1063-5157            Impact factor:   9.160


  27 in total

1.  Statistically based postprocessing of phylogenetic analysis by clustering.

Authors:  Cara Stockham; Li-San Wang; Tandy Warnow
Journal:  Bioinformatics       Date:  2002       Impact factor: 6.937

2.  Let them fall where they may: congruence analysis in massive phylogenetically messy data sets.

Authors:  Jessica W Leigh; Klaus Schliep; Philippe Lopez; Eric Bapteste
Journal:  Mol Biol Evol       Date:  2011-04-27       Impact factor: 16.240

3.  The devil in the details: interactions between the branch-length prior and likelihood model affect node support and branch lengths in the phylogeny of the Psoraceae.

Authors:  Stefan Ekman; Rakel Blaalid
Journal:  Syst Biol       Date:  2011-03-24       Impact factor: 15.683

4.  Information geometry for phylogenetic trees.

Authors:  M K Garba; T M W Nye; J Lueg; S F Huckemann
Journal:  J Math Biol       Date:  2021-02-15       Impact factor: 2.259

5.  RevBayes: Bayesian Phylogenetic Inference Using Graphical Models and an Interactive Model-Specification Language.

Authors:  Sebastian Höhna; Michael J Landis; Tracy A Heath; Bastien Boussau; Nicolas Lartillot; Brian R Moore; John P Huelsenbeck; Fredrik Ronquist
Journal:  Syst Biol       Date:  2016-05-28       Impact factor: 15.683

6.  ON CONSENSUS, COLLAPSIBILITY, AND CLADE CONCORDANCE.

Authors:  Kevin C Nixon; James M Carpenter
Journal:  Cladistics       Date:  1996-12       Impact factor: 5.254

7.  Hierarchical Clustering With Prototypes via Minimax Linkage.

Authors:  Jacob Bien; Robert Tibshirani
Journal:  J Am Stat Assoc       Date:  2011       Impact factor: 5.033

8.  Visualizing phylogenetic tree landscapes.

Authors:  James C Wilgenbusch; Wen Huang; Kyle A Gallivan
Journal:  BMC Bioinformatics       Date:  2017-02-02       Impact factor: 3.169

9.  Parsimony, not Bayesian analysis, recovers more stratigraphically congruent phylogenetic trees.

Authors:  Robert S Sansom; Peter G Choate; Joseph N Keating; Emma Randle
Journal:  Biol Lett       Date:  2018-06       Impact factor: 3.703

View more
  1 in total

1.  Using Information Theory to Detect Rogue Taxa and Improve Consensus Trees.

Authors:  Martin R Smith
Journal:  Syst Biol       Date:  2022-08-10       Impact factor: 9.160

  1 in total

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