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.