SUMMARY: Nanopore sequencing measures ionic current as native DNA or RNA molecules move through a biological pore. The resulting ionic current changes are inferred into sequence by Oxford Nanopore Technologies' Dorado basecaller. These data permit direct analysis of nucleotide sequences and modifications. The Dorado basecaller also outputs a move-table that contains approximate mappings between ionic current signal and basecalled sequence. This ionic current information can be visualized at specific positions given the alignment between a read sequence and a reference sequence. We present CurrentView, a fast and user-friendly toolkit for reference-guided visualization of nanopore ionic current signals. CurrentView uses conventional sequence alignment and move-table information from BAM files and signal information from ONT POD5 files to extract and visualize ionic current traces at specific positions. The toolkit supports simultaneous comparison across multiple experimental conditions, computes summary statistics through kernel density estimation and histograms, and enables visual analysis of signal patterns associated with modifications or sequence context. Notably, CurrentView can visualize and analyze more than two conditions at once. It supports UMAP dimensionality reduction and Gaussian Mixture Model (GMM) clustering, enabling the identification of distinct signal populations across experimental groups. CurrentView is available as both a Python API and an exploratory interactive web application, allowing researchers to rapidly inspect ionic current patterns and compare conditions. AVAILABILITY AND IMPLEMENTATION: CurrentView is fully open-source and available on GitHub https://github.com/genometechlab/currentview. The repository includes full documentation, an installation guide, usage instructions, and an example Jupyter notebook showing typical use cases similar to the one presented in the manuscript.

MOTIVATION: Nucleotide modification status can be decoded from the Oxford Nanopore Technologies nanopore-sequencing ionic current signals. Although various algorithms have been developed for nanopore-sequencing-based modification analysis, more detailed characterizations, such as modification numbers, corresponding signal levels and proportions are still lacking. RESULTS: We present a framework for the unsupervised determination of the number of nucleotide modifications from nanopore-sequencing readouts. We demonstrate the approach can effectively recapitulate the number of modifications, the corresponding ionic current signal levels, as well as mixing proportions under both DNA and RNA contexts. We further show, by integrating information from multiple detected modification regions, that the modification status of DNA and RNA molecules can be inferred. This method forms a key step of de novo characterization of nucleotide modifications, shedding light on the interpretation of various biological questions. AVAILABILITY AND IMPLEMENTATION: Modified nanopolish: https://github.com/adbailey4/nanopolish/tree/cigar_output. All other codes used to reproduce the results: https://github.com/hd2326/ModificationNumber. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.