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How to validate phylogenetic trees? A stepwise procedure

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Data Science, Classification, and Related Methods

Summary

In this paper, I review some of the methods and tests currently available to validate trees, focussing on phylogenetic trees (dendrograms and cladograms). I first present some of the more commonly used techniques to compare a tree with the data it is derived from (internal validation), or compare a tree to another tree or to more than one (external validation). I also discuss some of the advantages of performing combined (total evidence) versus separate analyses (consensus) of independent data sets for validation purposes. A stepwise validation procedure defined across all levels of comparison is introduced, along with a corresponding statistical test: A phylogeny will be said to be globally validated only if it satisfies all the tests. An application to the phylogeny of kangaroos is presented to illustrate the stepwise procedure.

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References

  • Adams, F. N., III. (1972): Consensus techniques and the comparison of taxonomic trees Systematic Zoology, 21, 390–397.

    Google Scholar 

  • Alroy. J. (1994): Four permutation tests for the presence of phytogenetic structure, Systematic Biology, 43, 430–437.

    Google Scholar 

  • Anderbcrg, A. and Tehler, A. (1990): Consensus trees, a necessity in taxonomic practice, Cladistics, 6, 399–402.

    Article  Google Scholar 

  • Archie, J. W. (1989a): A randomization test for phytogenetic information in systematic data Systematic Zoology, 38, 219–252.

    Google Scholar 

  • Archie, J. W. (1989b): Homoplasy excess ratios: New indices for measuring levels of homoplasy in phytogenetic systematics and a critique of the consistency index, Systematic Zoology, 38, 253–269.

    Article  Google Scholar 

  • Archie, J. W. (1989c): Phylogenies of plant families: A demonstration of phylogenetic randomness in DNA sequence data derived from proteins, Evolution, 43, 1796–1800.

    Article  Google Scholar 

  • Archie, J. W. (1990): Homoplasy excess statistics and retention indices: A reply to Farris Systematic Zoology, 39, 169–174.

    Google Scholar 

  • Archie, J. W. and Felsenstein, J. (1993): The number of evolutionary steps on random and minimum lengths trees for random evolutionary data. Theoretical Population Biology, 43, 52–79.

    Article  MATH  Google Scholar 

  • Bandelt. H. J. (1995): Combination of data in phylogenetic analysis Plant Systematics and Evolution Supplementum 9, 355–361.

    Google Scholar 

  • Barrett, M. et al. (1991): Against consensus Systematic Zoology 40, 486–493.

    Google Scholar 

  • Barrett, M. et al. (1993): Crusade’? A response to Nelson Systematic Biology 42, 216–217.

    Google Scholar 

  • Barthélemy, J.-P. and McMorris, F. R. (1986): The median procedure for n-trees Journal of Classification 3, 329–334.

    Google Scholar 

  • Baum, B. R. (1992): Combining trees as a way of combining data for phylogenetic inference, and the desirability of combining gene trees, Taxon, 41, 3–10.

    Article  Google Scholar 

  • Baum, B. R. and Ragan, M. A. (1993): Reply to A. G. Rodrigo’s “A comment on Baum’s method for combining phylogenetic trees, Taxon, 42, 637–640.

    Article  Google Scholar 

  • Baverstock, P. R. et al. (1989): Albumin immunologic relationships of the Macropodidae (Marsupialia) Systematic Zoology 38, 38–50.

    Google Scholar 

  • Berry, V. and Gascuel, O. (1996): On the interpretation of bootstrap trees: Appropriate threshold of clade selection and induced gain, Molecular Biology and Evolution, 13, 999–1011.

    Article  Google Scholar 

  • Bledsoe, A. H. and Raikow, R. J. (1990): A quantitative assessment of congruence between molecular and nonmolecular estimates of phylogeny, Journal of Molecular Evolution, 30, 247–259.

    Article  Google Scholar 

  • Bleiweiss, R. et al. (1994): DNA-DNA hybridization-based phylogeny of “higher nonpasserines: Reevaluating a key portion of the avian family tree, Molecular Phylogenetics and Evolution, 3, 248–255.

    Article  Google Scholar 

  • Bock, II. H. (1985): On some significance tests in cluster analysis, Journal of Classification, 2, 77–108. Bosibud, H. M. and Bosibud, L. E. (1972): A metric for classifications, Taxon, 21, 607–613.

    Google Scholar 

  • Bourque, M. (1978): Arbres de Steiner et réseaux dont varie l’emplacement de certains sommets. Ph. D. Thesis, Département d’Informatique et de Recherche Operatiouelle, Unversité de Montréal, Montréal.

    Google Scholar 

  • Bremer, K. (1990): Combinable component consensus, Cladistics, 6, 369–372. Bremer, K. (1995): Branch support and tree stability, Cladistics, 10, 295–304. Brown, J. K. M. (1994): Probabilities of evolutionary trees, Systematic Biology, 43, 78–91.

    Google Scholar 

  • Bryant, H. N. (1992): The role of permutation tail probability tests in phylogenetic systematics Systematic Biology 41, 258–263.

    Google Scholar 

  • Bull, J. J. et al. (1993): Partitioning and combining data in phylogenetic analysis, Systematic Biology, 42, 384–397.

    Google Scholar 

  • Buneman, P. (1971): The recovery of trees from measures of dissimilarity. In: Mathematics in Archeological and Historical Sciences, Hodson, F. R. et al. (eds.), 387–395, Edinburgh University Press, Edinburgh.

    Google Scholar 

  • Buneman, P. (1974): A note on the metric properties of trees, Journal of Combinatorial Theory (B), 17, 48–50.

    Article  MathSciNet  MATH  Google Scholar 

  • Carpenter, J. M. (1992): Random cladistics Cladistics 8, 147–153.

    Google Scholar 

  • Carter, M. et al. (1990): On the distribution of lengths of evolutionary trees SIAM Journal of Discrete ai’lathematics 3, 38–47.

    Google Scholar 

  • Chìppindale, P. T. and Wiens, J. J. (1994): Weighting, partitioning, and combining characters in phylogenetic analysis, Systematic Biology, 43, 278–287.

    Google Scholar 

  • Colless, D. H. (1980): Congruence between morphometric and allozyme data for Menidia species: A reappraisal Systematic Zoology 29, 288–299 .

    Google Scholar 

  • Critchlow, D. E. et al. (1996): The triples distance for rooted bifurcating phylogenetic trees Systematic Biology 45, 323–334.

    Google Scholar 

  • Cucumel, G. and Lapointe, F.-J. (1997): Un test de la pertinence du consensus par une méthode de permutations. In: Actes des XXIXe journées de statistique 299–300, Carcassonne.

    Google Scholar 

  • Davis, J. I. (1993): Character removal as a means for assessing stability of clades, Cladistics, 9, 201–210.

    Article  Google Scholar 

  • Day, W. H. E. (1983a): The role of complexity in comparing classifications, Mathematical Biosciences, 66, 97–114.

    Article  MathSciNet  MATH  Google Scholar 

  • Day, W. H. E. (1983b): Distributions of distances between pairs of classifications. In: Numerical Taxonomy Felsenstein, J. (ed.), 127–131, Springer-Verlag, Berlin.

    Google Scholar 

  • Day, W. H. E. (1983c): Computationally difficult parsimony problems in phylogenetic systematics Journal of Theoretical Biology 103, 429–438.

    Google Scholar 

  • Day, W. H. E. (1986): Analysis of quartet dissimilarity measures between undirected phylogenetic trees Systematic Zoology 35, 325–333.

    Google Scholar 

  • Day, W. H. E. (1987): Computational complexity of inferring phylogenies from dissimilarity matrices Bulletin of Mathematical Biology 49, 461–467.

    Google Scholar 

  • Day, W. H. E. and McMorris, F. R. (1985): A formalization of consensus index methods Bulletin of Mathematical Biology 47, 215–229.

    Google Scholar 

  • de Queiroz, A. (1993): For consensus (sometimes) Systematic Biology 42, 368–372.

    Google Scholar 

  • de Queiroz, A. et al. (1995): Separate versus combined analysis of phylogenetic evidence Annual Review of Ecology and Systematics 26, 657–681.

    Google Scholar 

  • Dopazo, J. (1994): Estimating errors and confidence intervals for branch lengths in phylogenetic tres by a bootstrap approach. Journal of Molecular Evolution, 38, 300–304.

    Article  Google Scholar 

  • Dubes, R. and Jain, A. K. (1979): Validity studies in clustering methodologies, Pattern Recognition, 11, 235–254.

    Article  MATH  Google Scholar 

  • Dwass, M. (1957): Modified randomization tests for nonparametric hypotheses Annals of Mathematics and Statistics 28, 181–187.

    Google Scholar 

  • Edgington, E. S. (1995): Randomization tests, 3rd Edition, Revised and Expanded. Marcel Dekker, New York.

    Google Scholar 

  • Eernisse, D. J. and Kluge, A. G. (1993): Taxonomic congruence versus total evidence, and the phylogeny of amniotes inferred from fossils, molecules and morphology, Molecular Biology and Evolution, 10, 1170–1195.

    Google Scholar 

  • Efron, B. (1979): Bootstrapping methods: Another look at the jackknife Annals of Statistics 7, 1–26.

    Google Scholar 

  • Efron, B. and Gong, G. (1983): A leisurely look at the bootstrap, the jackknife, and cross-validation American Statistician 37, 36–48.

    Google Scholar 

  • Efron, B. and Tibshirani, R. J. (1993): An introduction to the bootstrap, Chapman and Hall, New York.

    Google Scholar 

  • Efron, B. et al. (1996): Bootstrap confidence levels for phylogenetic trees Proceedings of the National Academy of Sciences USA93, 13429–13434.

    Google Scholar 

  • Estabrook, G. F. (1992): Evaluating undirected positional congruence of individual taxa between two estimates of the phylogenetic tree for a group of taxa, Systematic Biology, 41, 172–177.

    Google Scholar 

  • Estabrook, G. F. et al. (1985): Comparison of undirected phylogenetic trees based ou subtrees of four evolutionary units, Systematic Zoology, 34, 193–200.

    Article  Google Scholar 

  • Faith, D. P. (1991): Cladistic permutation tests for monophyly and nonmonophyly, Systematic Zoology, 40, 366–375.

    Article  Google Scholar 

  • Faith, D. P. (1992): Ou corroboration: A reply to Carpenter Cladistics 8, 265–273.

    Google Scholar 

  • Faith, D. P. and Ballard, J. W. O. (1994): Length differences topology-dependent tests: A response to Källersjö et al, Cladistics, 10, 57–64.

    Article  Google Scholar 

  • Faith, D. P. and Belbin, L. (1986): Comparison of classifications using measures intermediate between metric dissimilarity and consensus similarity, Journal of Classification, 3, 257–280.

    Article  MATH  Google Scholar 

  • Faith, D. P. and Cranston, P. S. (1991): Could a cladogram this short have arisen by chance alone? on permutation tests for cladistic structure, Cladistics, 71–28.

    Article  Google Scholar 

  • Faith, D. P. and Trueman, J. W. H. (1996): When the topology-dependent permutation test (T-PTP) for monophyly returns significant support for monophyly, should that be equated with (a) rejecting a null hypothesis of nonmonophyly, (b) rejecting a null hypothesis of “no structure,” (c) failing to falsify a hypothesis of monophyly, or (d) none of the above? Systematic Biology, 45, 580–586.

    Article  Google Scholar 

  • Farris, J. S. (1989a): The retention index and the resealed consistency index, Cladistics, 5, 417–419. Farris, J. S. (1989b): The retention index and homoplasy excess, Systematic Zoology, 38, 406–407. Farris, J. S. (1991): Excess homoplasy ratios, Cladistics, 7,81–91.

    Article  Google Scholar 

  • Farris, J. S. et al. (1995a): Constructing a significance test for incongruence Systematic Biology44, 570572.

    Google Scholar 

  • Farris, J. S. et al. (1995b): Testing significance of incongruencies, Cladistics, 10, 315–370. Felsenstein, J. (1978): The number of evolutionary trees, Systematic Zoology, 27, 27–33.

    Google Scholar 

  • Felsenstein, J. (1985): Confidence limits on phylogenies: An approach using the bootstrap, Evolution, 39, 783–791.

    Article  Google Scholar 

  • Felsenstein, J. (1993): PHYLIP: Phylogeny inference package, version 3.5c, distributed by the author, University of Washington, Seattle.

    Google Scholar 

  • Felsenstein, J. and Kishino, H. (1993): Is there something wrong with the bootstrap on phylogenies? A reply to Hillis and Bull, Systematic Biology, 42, 193–200.

    Google Scholar 

  • Finden, C. R. and Gordon, A. D. (1985): Obtaining common pruned trees Journal of Classification 2, 225–276.

    Google Scholar 

  • Fowlkes, E. B. and Mallows, C. L. (1983): A method for comparing two hierarchical clusterings, Journal.

    Google Scholar 

  • of the American Statistical Association,78, 553–569.

    Google Scholar 

  • Pumas, G. W. (1984): The generation of random, binary unordered trees Journal of Classification 1 187–233.

    Google Scholar 

  • Goloboff, P. (1991a): Homoplasy and the choice among cladograms,•Cladistics, 7, 215–232. Goloboff, P. (1991b): Random data, homoplasy and information, Cladistics,7 395–406.

    Article  Google Scholar 

  • Gordon, A. D. (1986): Consensus supertrees: the synthesis of rooted trees containing overlapping sets of labeled leaves, Journal of Classification, 3, 335–348.

    Article  MathSciNet  MATH  Google Scholar 

  • Gordon, A. D. (1987): A review of hierarchical classifications Journal of the Royal Statistical Society (A)150, 119–137.

    Google Scholar 

  • Gower, J. C. (1983): Comparing classifications. In: Numerical Taxonomy, Felsenstein, J. (ed.), 137–155, Springer-Verlag, Berlin.

    Chapter  Google Scholar 

  • Graham, R. L. and Foulds, L. R. (1982): Unlikelihood that minimal phylogenies for a realistic biological study can be constructed in reasonable computational time, Mathematical Biosciences, 60, 133–142.

    Google Scholar 

  • Hall, P. and Martin, M. A. (1988): On bootstrap resampling and iterations Biometrika 75, 661–671.

    Google Scholar 

  • Harding, E. F. (1971): The probabilities of rooted tree-shapes generated by random bifurcations Advances in Applied Probability 4, 44–77.

    Google Scholar 

  • -Iarshman, J. (1994): The effect of irrelevant characters on bootstrap values, Systematic Biology, 43, 419–424.

    Google Scholar 

  • Hartigan, J. A. (1967): Representation of similarity matrices by trees Journal of the American Statistical Association 62, 1140–1158.

    Google Scholar 

  • Hedges, S. B. (1992): The number of replications needed for accurate estimation of the bootstrap P value in phylogenetic studies, Molecular Biology and Evolution, 9, 366–369.

    Google Scholar 

  • Hendy, M. D. et al. (1984): Comparing trees with pendant vertices labelled SIAM Journal in Applied Mathematics 44, 1054–1065.

    Google Scholar 

  • Hillis, D. M. (1987): Molecular versus morphological approaches to systematics Annual Review of Ecology and Systematics 18, 23–42.

    Google Scholar 

  • Hillis, D. M. (1991): Discriminatin g between phylogenetic signal and random noise in DNA sequences, In: Phylogenetic analysis of DNA sequences, Miyamoto, M. M. and Cracraft, J. (eds.), 278–294, Oxford University Press, New York.

    Google Scholar 

  • Hillis, D. M. (1995): Approaches for assessing phylogenetic accuracy Systematic Biology 44, 3–16.

    Google Scholar 

  • Hillis, D. M. and Bull, J. J. (1993): An empirical test of bootstrapping as a method for assessing confidence in phylogenetic analysis, Systematic Biology, 42, 182–192.

    Google Scholar 

  • Hubert, L. J. and Baker, F. B. (1977): The comparison and fitting of given classification schemes Journal of Mathematical Psychology 16, 233–253.

    Google Scholar 

  • uelsenbeck, J. P. (1995): Performance of phylogenetic methods in simulation, Systematic Biology, 44, 17–48.

    Google Scholar 

  • Huelsenbeck, J. P. and Bull, J. J. (1996): A likelihood ratio test for detection of conflicting phylogenetic signal, Systematic Biology, 45, 92–98.

    Article  Google Scholar 

  • Huelsenbeck, J. P. et al. (1994): Is character weighting a panacea for the problem of data heterogeneity in phylogenetic analysis?, Systematic Biology, 43, 288–291.

    Google Scholar 

  • Huelsenbeck, J. P. et al. (1995): Parametric bootstrapping in molecular phylogenetics: Applications and performance, In: Molecular Zoology: Strategies and Protocols, Ferraris, J and Palumbi, S. (eds.), Wiley, New York.

    Google Scholar 

  • Huelsenbeck, J. P. et al. (1996): Combining data in phylogenetic analysis, Trends in Ecology and Evolution, 11, 152–158.

    Article  Google Scholar 

  • Jardine, C. J. et al. (1967): The structure and construction of taxonomic hierarchies Mathematical Biosciences 1, 173–179.

    Google Scholar 

  • Källersjö, M. et al. (1992): Skewness and permutation Cladistics8, 275–287.

    Google Scholar 

  • Kim, J. (1993): Improving the accuracy of phylogenetic estimation by combining different methods, Systematic Biology, 42, 331–340.

    Google Scholar 

  • Kirsch, J. A. W. et al. (1995): Resolution of portions of the kangaroo phylogeny (Marsupialia: Macropodidae) using DNA hybridization Biological Journal of the Linnean Society 55, 309–328.

    Google Scholar 

  • Kirsch, J. A. W. et al. (1997): DNA-hybridisation studies of marsupials and their implications for metatherian classification. Australian Journal of Zoology, in press.

    Google Scholar 

  • Klassen, G. J. et al. (1991): Consistency indices and random data Systematic Zoology 40, 446–457.

    Google Scholar 

  • Kluge, A. G. (1989): A concern for evidence and a phylogenetic hypothesis of relationships among Epicrates (Boidae, Serpentes) Systematic Biology 38, 7–25.

    Google Scholar 

  • Kluge, A. G. and Farris, J. S. (1969): Quantitative phyletics and the evolution of anurans Systematic Zoology 18, 1–32.

    Google Scholar 

  • Krajewski, C. and Dickerman, A. W. (1990): Bootstrap analysis of phylogenetic trees derived from DNA hybridization matrices, Systematic Zoology, 39, 383–390.

    Article  Google Scholar 

  • Lanyon, S. (1985): Detecting internal inconsistencies in distance data Systematic Zoology 34, 397–403.

    Google Scholar 

  • Lanyon, S. (1993): Phylogenetic frameworks: Towards a firmer foundation for the comparative approach Biological Journal of the Linnean Society 49, 45–61.

    Google Scholar 

  • Lapointe, F.-J. and Cucumel, G. (1997): The average consensus procedure: combination of weighted trees containing identical or overlapping sets of objects, Systematic Biology, 46, 306–312.

    Article  Google Scholar 

  • Lapointe, F.-J. and Legendre, P. (1990): A statistical framework to test the consensus of two nested classifications, Systematic Zoology, 39, 1–13.

    Article  Google Scholar 

  • Lapointe, F.-J. and Legendre, P. (1991): The generation of random ultrametric matrices representing dendrograms, Journal of Classification, 8, 177–200.

    Article  Google Scholar 

  • Lapointe, F.-J. and Legendre, P. (1992a): A statistical framework to test the consensus among additive trees (cladograms), Systematic Biology, 41, 158–171.

    Google Scholar 

  • Lapointe, F.-J. and Legendre, P. (1992b): Statistical significance of the matrix correlation coefficient for comparing independent phylogenetic trees, Systematic Biology, 41, 378–384.

    Google Scholar 

  • Lapointe, F.-J. and Legendre, P. (1994): A classification of pure. malt Scotch whiskies Applied Statistics 43, 237–257.

    Google Scholar 

  • Lapointe, F.-J. and Kirsch, J. A. W. (1995): Estimating phylogenies from lacunose distance matrices, with special reference to DNA hybridization data, Molecular Biology and Evolution, 12, 266–284.

    Google Scholar 

  • Lapointe, F.-J. and Legendre, P. (1995): Comparison tests for dendrograms: A comparative evaluation Journal of Classification 12, 265–282.

    Google Scholar 

  • Lapointe, F.-J. et al. (1994): Jackknifing of weighted trees: Validation of phylogenies reconstructed from distances matrices, Molecular Phylogenetics and Evolution, 3, 256–267.

    Article  Google Scholar 

  • Leclerc, B. and Cucumel, G. (1987): Consensus en classification: Une revue bibliographique Mathématiques et Sciences Humaines 100, 109–128.

    Google Scholar 

  • Lecointre, G. H. et al. (1993): Species sampling has a major impact on phylogenetic inference Molecular Phylogenetics and Evolution 2, 205–224.

    Google Scholar 

  • Lefkovitch, L. P. (1985): Euclidean consensus dendrograms and other classification structures Mathematical Biosciences 74, 1–15.

    Google Scholar 

  • Le Quesne, W. (1989): Frequency distributions of lengths of possible networks from a data matrix Cladistics 5, 395–407.

    Google Scholar 

  • Li, W.-H. and Guoy, M. (1991): Statistical methods for testing phylogenies, In: Phylogenetic analysis of DNA sequences Miyamoto, M. M. and Cracraft, J. (eds.), 249–277, Oxford University Press, New York.

    Google Scholar 

  • Li, W.-H. and Zharkikh, A. (1994): What is the bootstrap technique?, Systematic Biology, 43, 424–430. Li, W.-H. and Zharkikh, A. (1995): Statistical tests of DNA phylogenies, Systematic Biology, 44, 49–63.

    Google Scholar 

  • Ling, R. F. (1973): A probability theory of cluster analysis Journal of the American Statistical Association 68, 159–164.

    Google Scholar 

  • Mantel, N. (1967): The detection of disease clustering and a generalized regression approach Cancer Research 27, 209–220.

    Google Scholar 

  • Margush, T. (1982): Distances between trees Discrete Applied Mathematics 4, 281–290.

    Google Scholar 

  • Margush, T. and McMorris, F. R. (1981): Consensus n-trees, Bulletin of Mathematical Biology, 43, 239244.

    Google Scholar 

  • Marshall, C. R. (1991): Statistical tests and bootstrapping: Assessing the reliability of phylogenies based on distance data, Molecular Biology and Evolution, 8, 386–391.

    Google Scholar 

  • Mason-Gamer, R. J. and Kellogg, E. K. (1996): Testing for phylogenetic conflict among molecular data.

    Google Scholar 

  • sets in the tribe Triticeae (Gramineae), Systematic Biology,45 524–545.

    Google Scholar 

  • McMorris, F. R. (1985): Axioms for consensus functions ou undirected phylogenetic trees Mathematical Biosciences 74 17–21.

    Google Scholar 

  • McMorris, F. R. et al. (1983): A view of some consensus methods for trees. In: Numerical Taxonomy Felsenstein, J. (ed.), 122–126, Springer-Verlag, Berlin.

    Google Scholar 

  • McMorris, F. R. and Neumann, D. (1983): Consensus functions defined on trees Mathematical Social Sciences 4 131–136.

    Google Scholar 

  • Meier, R. et al. (1991): Homoplasy slope ratio: A better measurement of observed homoplasy in cladistic analyses, Systematic Zoology, 40, 74–88.

    Article  Google Scholar 

  • Mickevich, M. F. (1978): Taxonomic congruence, Systematic Zoology, 27, 143–158.

    Article  Google Scholar 

  • Milligan, G. W. (1981): A Monte-Carlo study of 30 internal criterion measures for cluster-analysis, Psychometrika, 46, 187–195.

    Article  MathSciNet  MATH  Google Scholar 

  • Miyamoto, M. M. (1985): Consensus cladograms and general classifications Cladistics 1186–189.

    Google Scholar 

  • Miyamoto, M. M. et al. (1994): A congruence test of reliability using linked mitochondria) DNA sequences, Systematic Biology, 43, 236–249.

    Google Scholar 

  • Miyamoto, M. M. and Fitch, W. M. (1995): Testing species phylogenies and phylogenetic methods with congruence, Systematic Biology, 44, 64–76.

    Google Scholar 

  • Mueller, L. D. and Ayala, F. J. (1982): Estimation and interpretation of genetic distances in empirical studies, Genetical Research, 40, 127–137.

    Article  Google Scholar 

  • Murtagh, F. (1984): Counting dendrograms: A survey, Discrete Applied Mathematics, 7, 191–199.

    Article  MathSciNet  MATH  Google Scholar 

  • Nelson, G. (1979): Cladistic analysis and synthesis: Principles and definitions, with a historical note on Adauson’s Famille des Plantes (1763–1764), Systematic Zoology, 28, 1–21.

    Article  Google Scholar 

  • Nelson, G. (1993): Why crusade against consensus? A reply to Barrett, Donoghue, and Sober Systematic Biology 42 215–216.

    Google Scholar 

  • Nemec, A. F. L. and Brinkburst, R. O. (1988): The Fowlkes-Mallows statistic and the comparison of two independently determined dendrograms, Canadian Journal of Fisheries and Aquatic Sciences, 45, 97 1975.

    Google Scholar 

  • Neumann, D. A. (1983): Faithful consensus methods for n-trees, Mathematical Biosciences, 63, 271–287. Nixon, K. C. and J. M. Carpenter. (1996): On simultaneous analysis, Cladistics, 12, 221–241.

    Google Scholar 

  • Oden, N. L. and Shao, K. T. (1984): An algorithm to equiprobably generate all directed trees with k labeled terminal nodes and unlabeled interior nodes, Bulletin of Mathematical Biology, 46, 379–387.

    MathSciNet  MATH  Google Scholar 

  • Olmstead, R. G. and Sweere, J. A. (1994): Combining data in phylogenetic systematics: An empirical approach using three molecular data sets in the Solanacae, Systematic Biology, 43, 467–481.

    Article  Google Scholar 

  • Omland, K. E. (1994): Character congruence between a molecular and a morphological phylogeny for dabbling ducks (Arras), Systematic Biology, 43, 369–386.

    Google Scholar 

  • Page, R. D. M. (1988): Quantitative cladistic biogeography: Constructing and comparing area cladograms, Systematic Zoology, 37, 254–270.

    Article  Google Scholar 

  • Page, R. D. M. (1991): Random dendrograms and null hypotheses in cladistic biogeography Systematic Zoology 40 54–62.

    Google Scholar 

  • Patterson, C. et al. (1993): Congruence between molecular and morphological phylogenies Annual Review of Ecology and Systematics 24 153–188.

    Google Scholar 

  • Penny, D. and Hendy, M. D. (1985a): The use of tree comparison metrics, Systematic Zoology, 34, 75–82. Penny, D. and Hendy, M. D. (1985b): Testing methods of evolutionary tree construction, Cladistics, 1, 266–278.

    Article  Google Scholar 

  • Penny, D. et al. (1982): Testing the theory of evolution by comparing phylogenetic trees constructed from five different protein sequences, Nature, 297, 197–200.

    Article  Google Scholar 

  • Penny, D. et al. (1992): Progress with methods for constructing evolutionary trees Trends in Ecology and Evolution 7, 73–79.

    Google Scholar 

  • Phillips, C. and Warnow, T. J. (1996): The asymmetric median tree–A new model for building consensus trees, Discrete Applied Mathematics, 71, 311–335.

    Article  MathSciNet  MATH  Google Scholar 

  • Phipps, J. B. (1975): The numbers of classifications, Canadian Journal of Botany, 54, 686–688.

    Article  Google Scholar 

  • Podani, J. and Dickinson, T. A. (1984): Comparison of dendrograms: A multivariate approach Canadian Journal of Botany 62 2765–2778.

    Google Scholar 

  • Poe, S. 1996. Data set incongrence and the phylogeny of Crocodilians, Systematic Biology, 45, 393–414.

    Article  Google Scholar 

  • Prager, E. M. and Wilson, A. C. (1976): Congruency of phylogenies derived from different proteins, Journal of Molecular Evolution, 9, 45–57.

    Article  Google Scholar 

  • Proskurowski, A. (1980): On the generation of binary trees Journal of the Association of Computing Machinery 27 1–2.

    Google Scholar 

  • Purvis, A. (1995a): A modification to Baum and Ragan’s method for combining phylogenetic trees, Systematic Biology, 44, 251–255.

    Google Scholar 

  • Purvis, A. (1995b): A composite estimate of primate phylogeny Philosophical Transactions of the Royal Society of London (B) 348 405–421.

    Google Scholar 

  • Quiroz, A. J. (1989): Fast random generation of binary, t-ary and other types of trees Journal of Classification 6 223–231.

    Google Scholar 

  • Ragan, M. A. (1992): Phylogeuetic inference based on matrix representation of trees Molecular Phylogenetics and Evolution 1 53–58.

    Google Scholar 

  • Robinson, D. F. (1971): Comparison of labeled trees with valency Three Journal of Combinatorial Theory 11 105–119.

    Google Scholar 

  • Robinson, D. F. and Foulds, L. R. (1979): Comparison of weighted labelled trees. In: Lecture Notes in Matehmatics Volume 748, 119–126, Springer-Verlag, Berlin.

    Google Scholar 

  • Robinson, D. F. and Foulds, L. R. (1981): Comparison of phylogenetic trees, Mathematical Biosciences, 53, 131–147.

    Article  MathSciNet  MATH  Google Scholar 

  • Rodrigo, A. G. (1993a): Calibrating the bootstrap test of monophyly, International Journal of Parasitology, 23, 507–514.

    Article  Google Scholar 

  • Rodrigo, A. G. (19936): A comment on Baum’s method for combining phylogenetic trees, Taxon, 42, 63 1636.

    Google Scholar 

  • Rodrigo, A. G. et al. (1993): A randomisation test of the null hypothesis that two cladograms are sample estimates of a parametric phylogenetic tree, New Zealand Journal of Botany, 31, 257–268.

    Article  Google Scholar 

  • Rohlf, F. J. (1974): Methods of comparing classifications, Annual Review of Ecology and Systematics, 5, 101–113.

    Article  Google Scholar 

  • Rohlf, F. J. (1982): Consensus indices for comparing classifications, Mathematical Biosciences, 59, 13 1144.

    Google Scholar 

  • Ronquist, F. (1996): Matrix representations of trees, redudancy and weighting, Systematic Biology, 45, 247–253.

    Article  Google Scholar 

  • Russo, C. A. M. et al. (1996): Efficiencies of different genes and different tree-building methods in recovering a known vertebrate phylogeny, Molecular Biology and Evolution, 13, 525–536.

    Article  Google Scholar 

  • Sanderson, M. J. (1989): Confidence limits on phylogenies: The bootstrap revisited, (laths es, 5, 113129.

    Google Scholar 

  • Sanderson, M. J. (1995): Objections of bootstrapping phylogenies: A critique, Systematic Biology, 44, 299–320.

    Google Scholar 

  • Savage, H. M. (1983): The shape of evolution: Systematic tree topology Biological Journal of the Linneae Society20, 225–244.

    Google Scholar 

  • Shao, K. and Rohlf, F. J. (1983): Sampling distribution of consensus indices when all bifurcating trees are equally likely. In: Numerical Taxonomy, Felsenstein, J. (ed.), 132–136, Springer-Verlag, Berlin.

    Chapter  Google Scholar 

  • Shoo, K. and Sokal, R. R. (1986): Significance tests of consensus indices, Systematic Zoology, 35, 58 2590.

    Google Scholar 

  • Simberloff, D. (1987): Calculating probabilities that cladograms match: A method of biogeographic inference, Systematic Zoology, 36, 175–195.

    Article  Google Scholar 

  • Simberloff, D. et al. (1981): There have been no statistical tests of cladistics biogeographical hypotheses. In: Vicariance Biogeography: A Critique, Nelson, G. and Rosen, D. E. (eds.), 40–63, Columbia University Press, New York.

    Google Scholar 

  • Sneath, P. H. A. (1967): Some statistical problems in numerical taxonomy, The Statistician, 17, 1–12.

    Article  Google Scholar 

  • Sokal R. R. and Rohlf, F. J. (1962): The comparison of dendrograms by objective methods, Taxon, 9, 3340.

    Google Scholar 

  • Sokal R. R. and Rohlf, F. J. (1981): Taxonomic congruence in the Leptopodomorpha re-examined Systematic Zoology30, 309–325.

    Google Scholar 

  • Steel, M. A. (1988): Distribution of the symmetric difference metric on phylogenetic trees SLANI.Journal of Discrete Mathematics1, 541–555.

    Google Scholar 

  • Steel, M. A. (1992): The complexity of reconstructing trees from qualitative characters and subtrees Journal of Classification9, 91–116.

    Google Scholar 

  • Steel, M. A. and Penny, D. (1993): Distribution of tree comparison metrics-Some new results Systematic Biology42, 126–141.

    Google Scholar 

  • Steel., M. A. et al. (1992): Significance of the length of the shortest tree Journal of Classification9, 6370.

    Google Scholar 

  • Stinebrickuer, R. (1982): S-consensus trees and indices Bulletin of Mathematical Biology46, 923–935.

    Google Scholar 

  • Stinebrickner, R. (1984): An extension of intersection methods from trees to dendrograms Systematic Zoology33, 381–386.

    Google Scholar 

  • Sullivan, J. (1996): Combining data with different distributions of among-site variation Systematic Biology45, 375–379.

    Google Scholar 

  • Swofford, D. L. (1991): When are phylogeny estimates from molecular and morphological data incongruent?, In: Phylogenetic analysis of DNA sequences, Miyamoto, M. M. and Cracraft, J. (eds.), 295–333, Oxford University Press, New York.

    Google Scholar 

  • Swofford, D. I. et al. (1996a): Phylogenetic inference, In: Molecular Systematics, 2nd edition, Hillis, D. M. et al. (eds.), 407–514, Sinauer, Sunderland.

    Google Scholar 

  • Swofford, D. L. et al. (19966): The topology-dependent permutation test for monophyly does not test for monophyly, Systeneatic Biology, 45, 575–579.

    Google Scholar 

  • Waterman, M. S. and Smith, T. F. (1978): On the similarity of dendrograms Journal of Theoretical Biology73, 789–800.

    Google Scholar 

  • Wiens, J. J. and Chippindale, P. T. (1994): Combining and weighting characters and the prior agreement approach revisited, Systematic Biology, 43, 564–566.

    Article  Google Scholar 

  • Wiens, J. J. and Reeder, T. W. (1995): Combining data sets with different numbers of taxa for phylogenetic analysis, Systematic Biology, 44, 548–558.

    Google Scholar 

  • Wilkinson, M. (1994): Common cladistic information and its consensus representation: Reduced Adams and reduced cladistic consensus trees and profiles, Systematic Biology, 43, 343–368.

    Google Scholar 

  • Wilkinson, M. (1996): Majority-rule reduced consensus trees and their use in boostrapping Molecular Biology and Evolution13, 437–444.

    Google Scholar 

  • Williams, D. M. (1994): Combining trees and combining data Taxon43, 449–453.

    Google Scholar 

  • Williams, W. T. and Clifford, FL T. (1971): On the comparison of two classifications ou the same set of elements Taxon20, 519–522.

    Google Scholar 

  • Zaretskii, K. (1965): Constructing a tree on the basis of a set of distances between the hanging vertices Uspekhi Mathematika Nauk20, 90–92. (in Russian).

    Google Scholar 

  • Zharkikh, A. and Li, W.-H. (1992a): Statistical properties of bootstrap estimation of phylogenetic variability from nucleotide sequences. I. Four taxa with a molecular clock, Molecular Biology and Evolution, 9, 1119–1147.

    Google Scholar 

  • Zharkikh, A. and Li, W.-H. (1992b): Statistical properties of bootstrap estimation of phylogenetic variability from nucleotide sequences. I1. Four taxa without a molecular clock. Journal of Molecular Evolution, 35, 356–366.

    Article  Google Scholar 

  • Zharkikh, A. and Li, W.-H. (1995): Estimation of confidence in phylogeny: The full-and-partial bootstrap technique, Molecular Phylogenetics and Evolution, 4, 44–63.

    Article  Google Scholar 

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  1. Département de sciences biologiques, Université de Montréal, C.P. 6128, Succursale centre-ville, Montréal, Québec, H3C 3J7, Canada

    François-Joseph Lapointe

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  1. François-Joseph Lapointe
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  1. The Institute of Statistical Mathematics, 4-6-7 Minami-Azabu, Minato-ku, Tokyo 106, Japan

    Chikio Hayashi , Noboru Ohsumi  & Yasumasa Baba ,  & 

  2. School of Management, Science University of Tokyo, 500 Shimokiyoku, Kuki, Saitama 346, Japan

    Keiji Yajima

  3. Institut für Statistik, Rheinisch-Westfälische Technische Hochschule (RWTH), D-52056, Aachen, Germany

    Hans-Hermann Bock

  4. Faculty of Environmental Science & Technology, Okayama University, 2-1-1 Tsushima-naka, Okayama 700, Japan

    Yutaka Tanaka

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Lapointe, FJ. (1998). How to validate phylogenetic trees? A stepwise procedure. In: Hayashi, C., Yajima, K., Bock, HH., Ohsumi, N., Tanaka, Y., Baba, Y. (eds) Data Science, Classification, and Related Methods. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Tokyo. https://doi.org/10.1007/978-4-431-65950-1_6

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