Fig. 3: Case study of Data 6 corresponding to I-BET treatment.
From: Deep transfer learning of cancer drug responses by integrating bulk and single-cell RNA-seq data
a From left to right: UMAPS visualizations of Data 6 colored by sample treatment types provided in the original study, ground-truth drug-response labels, predicted binary drug response labels, and predicted continuous drug response probability scores. b UMAP plot colored by sensitive (and resistant) gene scores derived from differentially expressed genes in the predicted and ground-truth sensitive (and resistant) cluster. Source data are provided as Source Data 7: sensitive and resistant DEG scores in predicted and ground truth sensitive and resistance cells in Data 6. c The plot displays the one-tail Pearson’s correlation test between the gene scores derived from the predicted and the ground-truth cell labels (n = 1,404). The error bands showed a 95% confidence interval of the regression. Source data are provided as Source Data 7: sensitive and resistant DEG scores in predicted and ground truth sensitive and resistance cells in Data 6. d Empirical test (n = 1,000) of correlation coefficient. The x-axis represents empirical correlations of differentially expressed gene scores, the y-axis represents frequencies, and the red dashed line represents scDEAL results. Abbreviation: differentially expressed gene (DEG).
