Snappy: fast identification of DNA methylation motifs based on oxford nanopore reads.

Motivation: Nowadays, DNA methylation in bacteria is studied mainly using single-molecule sequencing technologies like PacBio and Oxford Nanopore. In nanopore sequencing, calling of methylated positions is provided by special models implemented directly in basecallers. Prokaryotic DNA methyltransferases are site-specific enzymes, which catalyze methylation in specific methylation motifs. Inference of these motifs is usually performed using third party software like MEME providing classical motif enrichment based only on sequence data. However, currently used motif enrichment algorithms rely only on sequence data, and do not use additional base modification information provided by the basecaller. Results: Herein, we present a new tool Snappy, which is actually rethinking of the original Snapper algorithm but does not use any enrichment heuristics and does not require control sample sequencing. Snappy combines basecalling data processing with a new graph-based enrichment algorithm, thus significantly enhancing the enrichment sensitivity and accuracy. The versatility of the method was shown on both our and external data, representing different bacterial species with complex and simple methylome. Availability and implementation: Source code and documentation is hosted on GitHub (https://github.com/DNKonanov/ont-snappy) and Zenodo (zenodo.org/records/16731817). For accessibility, Snappy is installable from PyPi using "pip install ont-snappy" command.