Table 1.
Tools and strategies to detect base modifications in Nanopore data (HMM hidden Markov model, HPD hierarchical Dirichlet process, CNN convolutional neural network, LSTM long short-term memory, RNN recurrent neural network, SVM support vector machine)
| Tool | Base modifications | Strategy | Reference |
|---|---|---|---|
| Guppy | 5mCpG, 5mC (Dcm), 6mA (Dam) | Basecall | [45] |
| Taiyaki | – | Basecall | [45] |
| RepNano | BrdU | Basecall | [109] |
| D-Nascent | BrdU | HMM | [95] |
| Nanopolish | 5mCpG | HMM | [66] |
| Megalodon | 6mA, 5mCpG | HMM | [45] |
| signalAlign | 6mA, 5mC, 5hmC | HMM-HDP | [107] |
| DeepSignal | 6mA (Dam), 5mCpG | Neural network (CNN + classifier) | [110] |
| DeepMod | 6mA, 5mCpG | Neural network (LSTM-RNN) | [111] |
| mCaller | 6mA, 5mCpG | Neural network classifier | [108] |
| Tombo | 6mA (DNA), 5mC (RNA, DNA), de novo | Statistical test | [105] |
| NanoMod | de novo | Statistical test | [106] |
| EpiNano | m6A (RNA) | SVM | [112] |