Additional file 3: of A computational framework for complex disease stratification from multiple large-scale datasets

Table S7. Estimated accuracy and standard deviation of the RFE procedure. Table S8. Accuracy and Kappa values of the Random Forest models in the training set. Table S9. Performances values for the Random Forest model in the testing set. Figure S11. Relative importance of the top 20 predictors building the final model of the RF. The importance axis is scaled, with the mRNA expression of CD3D scaled to 100% and the methylation state of POLA2 to 0% (not shown). (DOCX 18 kb

Additional file 4: of A computational framework for complex disease stratification from multiple large-scale datasets

DIABLO sPLSDA model results. (DOCX 18966 kb