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Applications of a new subspace clustering algorithm (COSA) in medical systems biology

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Abstract

A novel clustering approach named Clustering Objects on Subsets of Attributes (COSA) has been proposed (Friedman and Meulman, (2004). Clustering objects on subsets of attributes. J. R. Statist. Soc. B 66, 1–25.) for unsupervised analysis of complex data sets. We demonstrate its usefulness in medical systems biology studies. Examples of metabolomics analyses are described as well as the unsupervised clustering based on the study of disease pathology and intervention effects in rats and humans. In comparison to principal components analysis and hierarchical clustering based on Euclidean distance, COSA shows an enhanced capability to trace partial similarities in groups of objects enabling a new discovery approach in systems biology as well as offering a unique approach to reveal common denominators of complex multi-factorial diseases in animal and human studies.

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Acknowledgments

We would like to thank Ms. Stacey Horrigan (BG Medicine) for her help during this project.

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Authors and Affiliations

  1. BG Medicine Inc., 610 Lincoln Street North, Waltham, MA, 02451, USA

    Doris Damian, Aram Adourian, Nicole Morel & Jan van der Greef

  2. VTT Technical Research Centre of Finland, Tietotie 2, PO Box 1500, Espoo, 02044 VTT, Finland

    Matej Orešič

  3. TNO Quality of life, PO Box 360, Zeist, 3700 AJ, The Netherlands

    Elwin Verheij, Age Smilde & Jan van der Greef

  4. Center for Medical Systems Biology, LACDR, Leiden University, Gorleaus Laboratories, Leiden, 2300 RA, The Netherlands

    Elwin Verheij & Jan van der Greef

  5. Data Theory Group, Faculty of Social and Behavioral Sciences, Leiden University, PO Box 9555, Leiden, 2300 RB, The Netherlands

    Jacqueline Meulman

  6. Nonlinear Dynamics of Natural Systems, Mathematical Institute, Leiden University, Niels Bohrweg 1, Leiden, 2333 CA, The Netherlands

    Jacqueline Meulman

  7. Department of Statistics and Stanford Linear Accelerator Center, Stanford University, Stanford, CA, 94305, USA

    Jerome Friedman

  8. Biosystems Data Analysis, Faculty of Sciences, University of Amsterdam, Nieuwe Achtergracht 166, Amsterdam, 1018 WV, The Netherlands

    Age Smilde

Authors
  1. Doris Damian
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  2. Matej Orešič
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  3. Elwin Verheij
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  4. Jacqueline Meulman
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  5. Jerome Friedman
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  6. Aram Adourian
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  7. Nicole Morel
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  8. Age Smilde
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  9. Jan van der Greef
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Corresponding authors

Correspondence to Matej Orešič or Jan van der Greef.

Additional information

Doris Damian, Matej Orešič, and Elwin Verheij contributed equally to this work.

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Damian, D., Orešič, M., Verheij, E. et al. Applications of a new subspace clustering algorithm (COSA) in medical systems biology. Metabolomics 3, 69–77 (2007). https://doi.org/10.1007/s11306-006-0045-z

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  • DOI: https://doi.org/10.1007/s11306-006-0045-z

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