Abstract

Background: High-throughput bisulfite sequencing (BS-seq), including whole-genome (WGBS) and reduced representation (RRBS), provides base-resolution DNA methylation. Despite mature command-line (CLI) workflows for alignment, methylation calling, and downstream analysis, many researchers without CLI experience face steep setup and reproducibility barriers. Existing GUIs often target array data or late-stage visualization and rarely assist with containerized, sequencing-oriented workflows that must run locally or on HPC.

Methods: We present methylEZ, an open-source, cross-platform, Python/Tkinter GUI that streamlines preparation of BS-seq analyses while preserving transparent, script-first execution. The application is organized in three modules: (1) preprocessing: FASTQ selection, read-pairing, and generation of validated samplesheets and ready-to-run commands for the nf-core/methylseq pipeline; (2) quality control assistance: automation of common asset preparation (reference indexing/dictionaries, BED to Picard interval_list conversion, BAM sorting/indexing) and batch scripts to drive Picard tools (e.g., CollectHsMetrics for capture designs) and samtools; and (3) downstream analysis templating: export of a parameterizable methylKit R script supporting coverage filters, DMS/DMR detection (with optional tiling), basic plots, and annotation. All artifacts (CLI strings, configs, and R scripts) are saved for inspection, version control, and reuse.

Results: We validated methylEZ on in-house methyl-capture BS-seq data. The GUI correctly produced nf-core/methylseq samplesheets and Nextflow commands, and the QC module batched reference/BAM preparations and coverage summaries via scripted Picard/samtools steps, reducing repetitive CLI interaction. The exported methylKit templates executed without error and generated interpretable differential methylation outputs and plots. methylEZ runs on macOS, Windows, and Linux; it is installable via pip from GitHub and requires Python 3; Tkinter is bundled on Windows/macOS and typically available via the Tk package on Linux.

Conclusions: methylEZ lowers the entry barrier to reproducible BS-seq by moving error-prone configuration and QC setup into a guided GUI while keeping execution explicit and auditable through exported commands and scripts. The tool complements web platforms (e.g., Galaxy) by emphasizing local/offline control and compatibility with community workflows (nf-core/methylseq) and statistical packages (methylKit). Planned extensions include in-GUI visualization (e.g., PCA, coverage histograms, volcano plots) and support for alternative methylation callers and statistical frameworks. methylEZ is released under GPL-3.0 at https://github.com/AlejRSosa/methylEZ