DeepSignal: detecting DNA methylation state from Nanopore sequencing reads using deep-learning

Peng Ni; Neng Huang; Feng Luo; Jianxin Wang

doi:10.1101/385849

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Abstract

The Oxford Nanopore sequencing enables to directly detect methylation sites in DNA from reads without extra laboratory techniques. In this study, we develop DeepSignal, a deep learning method to detect DNA methylated sites from Nanopore sequencing reads. DeepSignal construct features from both raw electrical signals and signal sequences in Nanopore reads. Testing on Nanopore reads of pUC19, E. coli and human, we show that DeepSignal can achieve both higher read level and genome level accuracy on detecting 6mA and 5mC methylation comparing to previous HMM based methods. Moreover, DeepSignal achieves similar performance cross different methylation bases and different methylation motifs. Furthermore, DeepSignal can detect 5mC and 6mA methylation states of genome sites with above 90% genome level accuracy under just 5X coverage using controlled methylation data.