Table 4.
Prediction performance on different data sets (AUROC).
| Enzyme type | Data set |
|||
|---|---|---|---|---|
| Data set
1 (P* > .6) 98 095 sites |
Data set
2 (P > .7) 75 720 sites |
Data set
3 (P > .8) 52 687 sites |
Data set
4 (P > .9) 27 646 sites |
|
| Erasers (FTO vs ALKBH5) | 0.873 | 0.873 | 0.872 | 0.888 |
| Writers (M3/M14 vs M16) | 0.889 | 0.888 | 0.911 | 0.877 |
Abbreviations: ALKBH5, ALKB homolog 5; AUROC, area under the receiver operating characteristics; FTO, fat mass and obesity–associated protein.
Four data sets were considered, corresponding to the experiment-validated RNA methylation sites from RMBase and also supported by WHISTLE prediction with probability greater than .6, .7, .8, and .9, respectively. The detailed performance of 5 different classification predictors (RF, SVM, GLM, Naïve Bayes, and decision tree) is presented in Supplementary Table S2.