IPF-LASSO: Integrative -Penalized Regression with Penalty Factors for Prediction Based on Multi-Omics Data

Figure 2

Panels (a), (b), and (c): difference between the median AUC of IPF-LASSO and the median AUC of the standard LASSO (red points) and between the median AUC of IPF-LASSO and the median AUC of SGL (black points) against simulation parameters. A positive difference indicates better performance of IPF-LASSO. Each point on the scatterplots represents one of the 6 + 33 = 39 simulation settings. Panel (a): against the absolute difference between the proportions of relevant variables in the two modalities. Panel (b): against the true model size . Panel (c): against a measure of the relative size of the modalities: /. Panel (d): Median number of selected variables for IPF-LASSO, standard LASSO, and SGL. Each boxplot represents the values obtained for the settings.

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