IDEAS home Printed from https://ideas.repec.org/a/bpj/sagmbi/v8y2009i1n22.html
   My bibliography  Save this article

Multilevel Comparison of Dendrograms: A New Method with an Application for Genetic Classifications

Author

Listed:
  • Podani János

    (Eotvos University)

  • Engloner Attila

    (Eotvos University)

  • Major Agnes

    (Hungarian Natural History Museum)

Abstract

Procedures are currently available for the evaluation of hierarchical classifications of produce tree dissimilarities or consensus dendrograms. Some tests of cluster validity operate by comparing all possible partitions from a tree with a reference partition. We propose an exhaustive search procedure to compare all partitions from one dendrogram with all partitions derived from the other to detect hierarchical levels at which the two dendrograms show maximum agreement. The method is illustrated using RAPD and microsatellite data in order to detect clones in reed populations. The utility of our approach is its ability to reveal extra information in different genetic data sets which would be hidden otherwise. The method is also useful in any field of science where hierarchical clustering is the main research tool and comparison of results is an objective. Artificial and actual dendrograms, together with randomly simulated trees were used to compare the performance of five classical coefficients of partition dissimilarity. The simulations showed that when meaningful group structure is lacking, then the five coefficients are in full disagreement, but they perform similarly otherwise.

Suggested Citation

  • Podani János & Engloner Attila & Major Agnes, 2009. "Multilevel Comparison of Dendrograms: A New Method with an Application for Genetic Classifications," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 8(1), pages 1-16, April.
    • Handle: RePEc:bpj:sagmbi:v:8:y:2009:i:1:n:22
    DOI: 10.2202/1544-6115.1443
    as

    Download full text from publisher

    File URL: https://doi.org/10.2202/1544-6115.1443
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.
    File URL: https://libkey.io/10.2202/1544-6115.1443?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Day, William H. E., 1981. "The complexity of computing metric distances between partitions," Mathematical Social Sciences, Elsevier, vol. 1(3), pages 269-287, May.
    2. Dean Neumann & Victor Norton, 1986. "Clustering and isolation in the consensus problem for partitions," Journal of Classification, Springer;The Classification Society, vol. 3(2), pages 281-297, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bruno Leclerc & Bernard Monjardet, 2010. "Aggregation and residuation," Post-Print halshs-00504982, HAL.
    2. Edward Brown & William Day, 1984. "A computationally efficient approximation to the nearest neighbor interchange metric," Journal of Classification, Springer;The Classification Society, vol. 1(1), pages 93-124, December.
    3. Peter Davison & Bruce Cameron & Edward F. Crawley, 2015. "Technology Portfolio Planning by Weighted Graph Analysis of System Architectures," Systems Engineering, John Wiley & Sons, vol. 18(1), pages 45-58, January.
    4. Daniel Faith & Lee Belbin, 1986. "Comparison of classifications using measures intermediate between metric dissimilarity and consensus similarity," Journal of Classification, Springer;The Classification Society, vol. 3(2), pages 257-280, September.
    5. Dinko Dimitrov & Thierry Marchant & Debasis Mishra, 2012. "Separability and aggregation of equivalence relations," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 51(1), pages 191-212, September.
    6. Alain Guénoche, 2011. "Consensus of partitions : a constructive approach," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 5(3), pages 215-229, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bpj:sagmbi:v:8:y:2009:i:1:n:22. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.degruyter.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.