Fig. 2

Screening process for DMRs potentially associated with CCC. Selection of DMR candidates in each of the three subsets sampled by replacement from the training sets. A Volcano plots examining associations between mean differences in AMF and q values. p values are calculated using Welch’s t-test on 600,000 bins for which >90% AMF values could be calculated in each subset. Negative log-transformed q values generated using FDR correction of p values plotted for the differences in AMF between good and poor CCC groups (converted to z-scores via standardization). The area above the dashed horizontal line indicates q values <0.05. The dashed vertical line indicates the absolute z-score value |z| of 2. When the mean AMF value is significantly lower in the good CCC group than in the poor CCC group, it is indicated as hypomethylation (blue). Conversely, a high mean AMF value is indicated as hypermethylation (red). B DMRs selected from each of the three subsets. A total of 1430 DMRs commonly included in the three subsets were used in additional filtering processes. C Top 500 DMRs in each subset selected from 1430 DMRs based on the significance of the q-value. A total of 256 DMRs included in top 500 of all subsets were selected as input values for the additional random forest classifier step. D PCA results of the 256 DMRs using the AMF values of all training set samples (poor CCC: \(n=\) 29; good CCC: \(n=\) 93). E PCA results of the 256 DMRs using the AMF values of the test set samples (poor CCC: \(n=\) 5; good CCC: \(n=\) 16). The PCA results of the test set were predicted using the learning test results based on the training set