Fig. 3.

In-sample predictive performance of kernel models. a Adjusted mean $R^2$ (Y-axis) of best kernel models over various numbers of the top biomarkers (X-axis) in the CpG (dark blue), miRNA (orange), and mRNA (light blue) omics over 50 Monte Carlo folds. The X-axis scale is logarithmic. b Bar plots of adjusted mean $R^2$ (Y-axis) for optimally tuned kernel predictive models using all combinations of omics (X-axis) over 50 Monte Carlo folds. The error bar gives a spread of one standard deviation around the mean adjusted $R^2$