Fig. 2. Validity evaluation of dimension reduction framework using advanced machine learning approaches and external syngeneic mouse models.

(A to C) Results from control samples. (A) Prediction accuracy of testing data over 10 replicates. Performance of our model was benchmarked by both linear and nonlinear supervised models, SGD classifier (SGDC), RFC, K-NN, and MLP. For the baseline methods, grid search was applied to tune each model’s parameters on the training set (60%). Model performance was measured on the testing data (20%). The difference in accuracy between methods was examined by the Mann-Whitney U test. (B) Contingency table summarizing ICB response predictions on 16 external control syngeneic mouse samples collected from two public studies used for validation. (C) Heatmap of the coefficient matrix of decomposition products. Bars on the right panel were derived from the basis matrix corresponding to the ICB response labels. (D to F) Results from post-ICB samples. (E) An additional 14 external post-ICB syngeneic mouse samples were collected from two studies for validation. Responder, R; nonresponder, NR.