1. Nat. Rev. Rheumatol. doi:10.1038/nrrheum.2017.220
Figure 4 Types of integrative approaches for unsupervised clustering analysis
Figure 4 | Types of integrative approaches for unsupervised clustering analysis. Integrative clustering approaches can be divided into four types, depending on whether a concatenation method or non-concatenation method is used, and whether the approach is based on statistical modelling (model-based) or on the transformation of data into a common feature space (transformation-based). Concatenation or non-concatenation approaches differ in the point in which the layers of information are combined (at an early stage of the process or at the very end stage, respectively). Transformation or model-based methods are statistically methods that are defined based on how the key clustering information is captured from the different datasets. The model-based methods model the data mathematically, whereas the transformation-based methods reduce the information down to features that summarize the original information.
Barturen, G. et al. (2018) Moving towards a molecular taxonomy of autoimmune rheumatic diseases
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