Samarakoon, H.; Kei Wan, Y.; Parameswaran, S.; Göke, J.; Gamaarachchi, H.; Deveson, I. W.

Nanopore sequencing by Oxford Nanopore Technologies (ONT) enables direct analysis of DNA and RNA by capturing raw electrical signals. Different nanopore chemistries have varied k-mer lengths, current levels, and standard deviations, which are stored in k-mer models. Particularly in cases where official models are lacking or unsuitable for specific sequencing conditions, tailored k-mer models are crucial to ensure precise signal-to-sequence alignment and interpretation. The process of transforming raw signals into nucleotide sequences, known as basecalling, is a fundamental step in nanopore sequencing. In this study, we leverage the basecaller\'s move table to create a lightweight denovo k-mer model for RNA004 chemistry. We showcase the effectiveness of our custom k-mer model through high alignment rates (97.48%) compared to larger default models. Additionally, our 5-mer model exhibits similar performance as the default 9-mer models in m6A methylation detection.