Towards inferring nanopore sequencing ionic currents from nucleotide chemical structures
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- Published on: December 2 2020
- Source: bioRxiv
The characteristic ionic currents of nucleotide kmers are commonly used in analyzing nanopore sequencing readouts.
We present a graph convolutional network-based deep learning framework for predicting kmer characteristic ionic currents from corresponding chemical structures.
We show such a framework can generalize the chemical information of the 5-methyl group from thymine to cytosine by correctly predicting 5-methylcytosine-containing DNA 6mers, thus shedding light on the de novo detection of nucleotide modifications.
