<i>memod-s</i>: a standardised workflow to explore and analyse prokaryotic methylation patterns for Nanopore sequencing data

<h4>Motivation</h4>Understanding the bacterial epigenome is increasingly recognised as essential for uncovering key mechanisms of gene regulation, host-pathogen interactions, and adaptation to environmental changes. Third-generation sequencing technologies, such as Oxford Nanopore, now enable the direct detection of DNA modifications, making genome-wide epigenomic investigations both feasible and cost-effective. However, analysing Nanopore sequencing data remains computationally intensive and requires multiple steps, which can be complex to integrate. Currently, no existing workflow combines these steps in a single, easy-to-use pipeline. Additionally, many available tools lack automated genome-wide methylation profiling with integrated visualisations and statistics.<h4>Results</h4>Here, we present <i>memod-s</i>, a Snakemake-based workflow that integrates multiple state-of-the-art tools to address these challenges. <i>memod-s</i> is a modular and user-friendly workflow that simplifies the entire Nanopore data analysis process-from basecalling and quality control to genome assembly, annotation, and methylation analysis. By integrating all essential steps into one cohesive pipeline and producing comprehensive genome-wide methylation profiles enriched with graphical visualisations and statistics, <i>memod-s</i> reduces the complexity of Nanopore data analysis and provides insights into bacterial methylation patterns and their potential biological implications.<h4>Availability and implementation</h4>The <i>memod-s</i> workflow is freely available as open source from the <i>memod-s</i> GitHub repository (https://github.com/AlessiaMarotta/memod-s).