Additional File 12.

Example of a decision tree for classification of tissue samples in appropriate disease classes. Heatmap illustrates expression values for 25 genes across 108 tissue samples and represents part of the heatmap shown in figure 2. A decision tree is a tree-like structure to relate gene expression measurements to sample phenotype class, with a view to deriving a predictive model. Nodes (rectangles) in the tree represent a test on gene expressions to derive a decision on a sample’s class, edges (arrows) indicate the expression level of the variable that can best distinguish the samples and leaves (or terminal nodes - circles) represent class predictions. The path from root to each terminal node equates to a list of conditions in the form of gene expression rules that can relate tissue samples to disease phenotype class.

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Ainali et al. BMC Genomics 2012 13:472   doi:10.1186/1471-2164-13-472