Fig. 2. Number of assays that can be accurately predicted using single profiling modalities.

All reported numbers are the median result of the five-fold cross-validation experiments run in the dataset. A Performance of individual modalities measured as the number of assays (vertical axis) predicted with AUROC above a certain threshold (horizontal axis). With higher AUROC thresholds, the number of assays that can be predicted decreases for all profiling modalities. We define accurate assays as those with AUROC greater than 0.9 (dashed vertical line in blue). B The Venn diagrams on the right show the number of accurate assays (median AUROC > 0.9) that are in common or unique to each profiling modality. The bar plot shows the distribution of assay types correctly predicted by single profiling modalities. C Distribution of performance of data modalities over all assays. Points are the median AUROC scores of n = 270 assays. Box plot elements: center line, median; box limits, upper and lower quartiles; whiskers, 1.5x interquartile range; points, all points presented using a swarmplot. D Number of assays well predicted (median AUROC > 0.9) by each individual modality (first row is the same as in Fig. 3B). E Performance of chemical structure features on the assay prediction task: graph convolutions are learned representations, while Morgan Fingerprints are classical representations. CS Chemical Structure, GE Gene Expression, MO Morphology, AUROC Area under the receiver operating characteristic, AUPRC Area under the precision recall curve, Conv convolutions, FP fingerprints.