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Mepylome: Ultra-Fast Methylation Array Analysis Toolkit

Mepylome is a high-performance Python toolkit tailored for parsing, processing, and analyzing methylation array IDAT files. Serving as a versatile library, Mepylome supports a wide range of methylation analysis tasks. It also includes an interactive GUI that enables users to generate UMAP plots and CNV plots (Copy Number Variation) directly from collections of IDAT files. Mepylome is designed for large-scale cohort processing and delivers substantial speed improvements over existing methylation analysis pipelines.

Mepylome is open source, and hosted at github: https://github.com/brj0/mepylome

✨ Key Highlights

• ⚡ Very fast processing engine

• 🧬 Supports Illumina 450k, EPIC, EPICv2, 27k, MSA48, and MM285 arrays

• 📊 CNV analysis with interactive Plotly visualizations

• 🧹 Clean API for large-scale cohort processing

• 🖥️ Optional GUI for UMAP + CNV exploration

• 🎯 Data inference: tumor purity estimation, MLH1 promoter methylation reports

• 🧪 Built-in QC including pOOBAH detection and quality metrics

Features

• Parsing of IDAT files

• Extraction of methylation signals

• Calculation of Copy Number Variations (CNV) with visualization using plotly

• Interactive CNV visualization in the browser

• CN-summary plots

• Supported Array Types

  • Illumina EPIC / EPICv2

  • Illumina 450k

  • Illumina 27k

  • Illumina MSA48

  • Illumina MM285 (Mouse)

• Significantly faster compared to:

  • minfi

  • conumee2

  • sesame

• pOOBAH-based probe filtering

• Sample- and probe-level quality metrics

• Tumor purity estimation from methylation beta values

• MLH1 promoter methylation report pages

• Interactive visualization of methylation across a gene or an arbitrary genomic region

• Methylation analysis tool with a graphical browser interface for:

  • UMAP analysis

  • CNV plots

  • Supervised classification

  Can be run from the command line with minimal setup or customized through a Python script.

Publication

This library is described in the following peer-reviewed publication:

https://doi.org/10.1002/aisy.202500778

Documentation outline

1. Installation instructions

2. The GUI, recommended for all new users

3. The tutorial, recommended for all new users

Contents:

• Installation
  • From PyPI
  • From Source
  • Uninstallation
  • Platform Compatibility
• User Guide: CLI / GUI
  • Graphical user interface: Quick demonstration
  • General Setup
  • Comand line interface
• Tutorial (library)
  • Setup
  • Parsing IDAT files
  • Manifest files
  • RawData
  • MethylData
  • Copy number variation (CNV)
  • Methylation Analysis
  • Supervised Classification
• Performance
  • Overview
  • Performance Comparison
  • How It Works
• API Reference
  • mepylome.dtypes.idat
  • mepylome.dtypes.manifests
  • mepylome.dtypes.beads
  • mepylome.dtypes.cnv
  • mepylome.dtypes.purity
  • mepylome.analysis.core
  • mepylome.analysis.utils
  • mepylome.analysis.classifiers

Indices and tables

• Index

• Module Index

• Search Page