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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)

From: Opportunities and challenges in long-read sequencing data analysis

ToolBase modificationsStrategyReference
Guppy5mCpG, 5mC (Dcm), 6mA (Dam)Basecall[45]
TaiyakiBasecall[45]
RepNanoBrdUBasecall[109]
D-NascentBrdUHMM[95]
Nanopolish5mCpGHMM[66]
Megalodon6mA, 5mCpGHMM[45]
signalAlign6mA, 5mC, 5hmCHMM-HDP[107]
DeepSignal6mA (Dam), 5mCpGNeural network (CNN + classifier)[110]
DeepMod6mA, 5mCpGNeural network (LSTM-RNN)[111]
mCaller6mA, 5mCpGNeural network classifier[108]
Tombo6mA (DNA), 5mC (RNA, DNA), de novoStatistical test[105]
NanoModde novoStatistical test[106]
EpiNanom6A (RNA)SVM[112]