Vladimír Boža, Eduard Batmendijn, Peter Perešíni, Viktória Hodorová, Hana Lichancová, Rastislav Rabatin, Broňa Brejová, Jozef Nosek, Tomáš Vinař. Precise Nanopore Signal Modeling Improves Unsupervised Single-Molecule Methylation Detection. In Proceedings of the 23rd Conference Information Technologies – Applications and Theory (ITAT 2023), 3498 volume of CEUR Workshop Proceedings, pp. 223-231, Tatranske Matliare, 2023.

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Base calling in nanopore sequencing is a difficult and computationally intensive problem, typically resulting in high error rates.
In many applications of nanopore sequencing, direct analysis of raw signal is a viable alternative. Dynamic time warping
(DTW) is an important building block for raw signal analysis. In this paper, we propose several improvements to DTW class
of algorithms to better account for specifics of nanopore signal modeling. We have implemented these improvements in a new
signal-to-reference alignment tool Nadavca. We demonstrate that Nadavca alignments improve unsupervised methylation
detection over Tombo. We also demonstrate that by providing additional information about the discriminative power of
positions in the signal, an otherwise unsupervised method can approach the accuracy of supervised models.
Availability and implementation: Nadavca is available under MIT license at https://github.com/fmfi-compbio/nadavca.
Nanopore sequencing data sets are available from ENA bioproject PRJEB64246. Jaminaea angkorensis reference genome
assembly is available from Zenodo https://doi.org/10.5281/zenodo.8145315