Fig. 3

Selection of major DMRs related to good CCC using a random forest classifier. A Flowchart of random forest classifier training and validation through repeated cross-validation using good CCC-related DMR candidates. For the entire training set (poor CCC: \(n=\) 29; good CCC: \(n=\) 93), AMF values of 256 pre-screened CCC-related DMR candidates were used for training. To validate the training results, predictions were made on pre-separated test set samples (poor CCC: \(n=\) 5; good CCC: \(n=\) 16). B ROC curves for the learning test results of the training set (blue) and the prediction results of the test set (red). C A box plot of the AMF distribution and annotations of good (red: \(n=\) 109) and poor CCC (violet: \(n=\) 34) groups. These correspond to the top 20 DMRs determined from the random forest classifier training results. D Pathway analysis results of the 20 DMRs associated with CCC