Hierarchical clustering was also successfully applied to the output of KODAMA to identify metabolic phenotypes in the plasma of patients with prostate cancer (Cacciatore et al., 2021) and visualize metabolic data for MYC- and AKT-driven prostate cancer (Priolo et al., 2014). This evidence concerns the gene AKT1 and Familial prostate cancer.