Vladimir Boza, Eduard Batmendijn, Peter Peresini, Viktoria Hodorova, Hana Lichancova, Rastislav Rabatin, Brona Brejova, Jozef Nosek, Tomas Vinar. Precise Nanopore Signal Modeling Improves Unsupervised Single-Molecule Methylation Detection. Technical Report 2023.07.13.548926, bioRxiv, 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, 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.