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Fig. 1 | BMC Genomics

Fig. 1

From: ACES: a machine learning toolbox for clustering analysis and visualization

Fig. 1

Overview of ACES. An example is used to show ACES. ACES loads a Saguaro formated file with several distance matrices, of which distance matrix 1 is chosen. Together with the clustering results shown in two colors (pink and blue), distance matrix 1 is visualized either in a 2D scatter plot or Heat Map view. The heat map is reordered by the clustering results. Also, ACES can load the corresponding attributes and predict their discriminative power shown on the screen, using the clusters. According to the prediction, IDH status and MGMT promoter status are selected and then visualized in the bottom scatter plots, as well as at the bottom line of localization in the heat map. The points are colored by their selected attribute label and clickable to view a full set of attribute information, which clearly demonstrate the relationship between selected attributes and the clusters results

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