methylEZ : a graphical user interface for differential methylation analysis in bisulfite sequencing data

Background High-throughput bisulfite sequencing (BS-seq), including whole-genome bisulfite sequencing (WGBS) and reduced representation bisulfite sequencing (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 graphic user interfaces (GUIs) often target array data or late-stage visualization and rarely assist with containerized, sequencing-oriented workflows that must run on high-performance computing (HPC) cluster or local workstations. 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: FAST-All with Quality (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, Browser Extensible Data (BED) to Picard interval_list conversion, Binary Alignment Map (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, differential methylation (DM) detection (with optional tiling), basic plots and annotation. All artifacts (CLI strings, configs and scripts) are saved for inspection, version control and reuse. Results We validated methylEZ on in-house methyl-capture BS-seq data and on publicly available BS-seq data. The GUI correctly produced nf-core/methylseq samplesheets and Nextflow commands, and the quality control (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. 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 offline control and compatibility with community workflows (nf-core/methylseq) and statistical packages (methylKit) on capable infrastructure. Planned extensions include in-GUI visualization ( e.g ., PCA, coverage histograms, volcano plots) and support for alternative callers and statistical frameworks. methylEZ is released under GPL-3.0.