Abstract
We developed a methodology that both facilitates and enhances the search for homogeneous subtypes in data. We applied this methodology to medical research on Osteoarthritis and Parkinson’s Disease and to chemoinformatics research on the chemical structure of molecule profiles. We release this methodology as the R SubtypeDiscovery package to enable reproducibility of our analyses. In this paper, we present the package implementation and we illustrate its output on molecular data from chemoinformatics. Our methodology includes different techniques to process the data, a computational approach repeating data modelling to select for a number of subtypes or a type of model, and additional methods to characterize, compare and evaluate the top ranking models. Therefore, this methodology does not solely cluster data but it also produces a complete set of results to conduct a subtype discovery analysis.
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Colas, F. et al. (2008). A Scenario Implementation in R for SubtypeDiscovery Examplified on Chemoinformatics Data. In: Margaria, T., Steffen, B. (eds) Leveraging Applications of Formal Methods, Verification and Validation. ISoLA 2008. Communications in Computer and Information Science, vol 17. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88479-8_48
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DOI: https://doi.org/10.1007/978-3-540-88479-8_48
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