A Guide to Enzymatic Targeted Methylation Sequencing Bioinformatics Workflow: Best Practices

We present a best-practices protocol for targeted DNA methylation sequencing analysis that integrates both bisulfite- and enzymatic-conversion approaches using Twist Bioscience technology. Building on established tools and vendor-recommended workflows, this protocol provides a standardized, fully reproducible framework that addresses current gaps in the implementation, documentation, and downstream integration of targeted methylation sequencing analyses. The workflow incorporates widely used open-source tools across two main stages: preprocessing (adapter trimming with Trim Galore and quality control via FastQC/MultiQC) and methylation calling (alignment with BWA-meth, duplicate marking using Picard, and methylation extraction with MethylDackel). Importantly, we extend existing workflows by introducing a structured third stage for downstream statistical analysis in R, including β-value calculation, differential methylation analysis with methylKit, principal component analysis, and tiling-based regional profiling, all embedded in a unified, reproducible pipeline. A key contribution of this protocol is the integration of multi-stage quality control checkpoints, harmonized parameterization, and explicit reporting of intermediate outputs, enabling transparency and reproducibility across all analytical steps. The modular design allows tool substitution and adaptation to different experimental contexts, including enzyme-based methylation methods, while maintaining consistency in data processing and interpretation. This guide provides step-by-step instructions, troubleshooting strategies, and examples of expected outputs, along with built-in statistical routines that generate comprehensive results, including methylation matrices, correlation analyses, differentially methylated region annotations, and publication-ready visualizations. The complete workflow requires approximately 9-27 hr for 10 samples (approximately 134.2 million reads per sample) on Linux systems and assumes moderate proficiency in command-line environments and R. In summary, this protocol offers a practical, transparent, and reproducible framework that standardizes targeted DNA methylation analysis and facilitates its application across diverse biological and clinical research settings. © 2026 The Author(s). Current Protocols published by Wiley Periodicals LLC.