# memod-s: a standardised workflow to explore and analyse prokaryotic methylation patterns for Nanopore sequencing data

## TL;DR

memod-s is a new workflow that simplifies analyzing bacterial DNA methylation patterns using Nanopore sequencing data.

## Contribution

memod-s introduces a unified, user-friendly pipeline for prokaryotic methylation analysis with integrated visualization and statistics.

## Key findings

- memod-s combines basecalling, assembly, and methylation analysis into one pipeline.
- The workflow provides genome-wide methylation profiles with visualizations and statistics.
- memod-s is open source and available for use in bacterial epigenomic studies.

## Abstract

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.

Here, we present memod-s, a Snakemake-based workflow that integrates multiple state-of-the-art tools to address these challenges. memod-s 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, memod-s reduces the complexity of Nanopore data analysis and provides insights into bacterial methylation patterns and their potential biological implications.

The memod-s workflow is freely available as open source from the memod-s GitHub repository (https://github.com/AlessiaMarotta/memod-s).