Extended Data Fig. 1: Overview of PERCEPTION model’s training data and features.

A) Cancer type distribution of the 318 cell lines used during the bulk expression training of PERCEPTION (step 1). B) Similarly, showing the cancer type distribution of the 169 cell lines used during the sc-expression training of PERCEPTION (step 2) C) The performance of PERCEPTION in predicting response in unseen cell lines when built via (1) pan-cancer models: all available cell lines (N = 169) are used for training the model, (2) Cancer-type specific: trained only on cell lines of the same cancer type as those used in the testing (N = 16 melanoma cell lines, 37 lung cancer cell lines and 15 breast cancer cell lines, as we used the PERCEPTION to predict the patient’s treatment response in three clinical trial cohorts from skin, lung, and breast cancer, we compared the pan-cancer model with these three individual cancer-type models). No statistical test was performed to compare groups. Error bars indicate the standard error of the mean (SEM), reflecting data variability. D) Major classes of mechanism of action of the 133 FDA-approved drugs that were studied here. No statistical test was performed to compare between groups. E) Top pathways enriched in frequently appearing features/genes in the PERCEPTION models. This is computed using a GSEA rank test across all hallmark pathways. To assess the statistical significance of these scores, a permutation test was performed.