Fig. 4

Prediction accuracy of tissue-specific cancer DNAm patterns from the H3K36me3 signal. a Left panel depicts a barplot of the AUC of seven different models (as obtained in the cross-validation model selection step) in predicting promoter DNA hypermethylation in cancer, for each of six different cancer types (COAD, KIRC, LIHC, LUAD, PAAD and BRCA), as indicated. High AUC values indicate better models. Right panel depicts the Akaike information criterion (AIC) values of each model in each cancer type. Lower AIC values indicate better models. b AUC values of optimal model in the mode selection (training) and blind test sets and for each cancer type. c For the model including all three histone signals as predictors, we plot the estimated z-statistics of each predictor of the trained model. Positive (negative) associations indicate that larger (lower) signal values correlate with increased promoter hypermethylation in cancer