How frequently do clusters occur in hierarchical clustering analysis? A graph theoretical approach to studying ties in proximity

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• 作者：Wilmer Leal ; Eugenio J. Llanos ; Guillermo Restrepo…
• 关键词：Ties in proximity ; Cluster stability ; Hierarchical cluster analysis (HCA) ; Dendrogram ; Cluster frequency ; Molecular descriptor
• 刊名：Journal of Cheminformatics
• 出版年：2016
• 出版时间：December 2016
• 年：2016
• 卷：8
• 期：1
• 全文大小：8,301 KB
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• 作者单位：Wilmer Leal (1) (2)
  Eugenio J. Llanos (1) (2) (3)
  Guillermo Restrepo (2) (4)
  Carlos F. Suárez (1) (5)
  Manuel Elkin Patarroyo (1) (6)
  
  1. Fundación Instituto de Inmunología de Colombia (FIDIC), Bogotá, Colombia
  2. Laboratorio de Química Teórica, Universidad de Pamplona, Pamplona, Colombia
  3. Corporación SCIO, Bogotá, Colombia
  4. Bioinformatics Group, Department of Computer Science, Universität Leipzig, Leipzig, Germany
  5. Universidad del Rosario, Bogotá, Colombia
  6. Universidad Nacional de Colombia, Bogotá, Colombia
  
• 刊物类别：Physics and Astronomy
• 刊物主题：Computer Applications in Chemistry
  Theoretical and Computational Chemistry
  Computational Biology/Bioinformatics
  Documentation and Information in Chemistry
  
• 出版者：Chemistry Central Ltd
• ISSN：1758-2946

文摘

Background Hierarchical cluster analysis (HCA) is a widely used classificatory technique in many areas of scientific knowledge. Applications usually yield a dendrogram from an HCA run over a given data set, using a grouping algorithm and a similarity measure. However, even when such parameters are fixed, ties in proximity (i.e. two equidistant clusters from a third one) may produce several different dendrograms, having different possible clustering patterns (different classifications). This situation is usually disregarded and conclusions are based on a single result, leading to questions concerning the permanence of clusters in all the resulting dendrograms; this happens, for example, when using HCA for grouping molecular descriptors to select that less similar ones in QSAR studies.