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methylation-analysis

Identify differential methylation between sample groups from Illumina beta-value matrices.

64|12|Updated Apr 7, 2026
Search Tags:#bioinformatics#qc#methylation#epigenomics#dmr#dmp#beta-values
One-click install
npx skills add https://github.com/MDhewei/bioinfor-claw --skill methylation-analysis
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: methylation-analysis
Source: https://github.com/MDhewei/bioinfor-claw/tree/main/multiomics-data-analysis/methylation-analysis
Command: npx skills add https://github.com/MDhewei/bioinfor-claw --skill methylation-analysis

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, numpy, matplotlib, scipy, and includes scripts (resource) components.

What problem does it solve?

DNA methylation datasets (beta-values) across samples require integrated QC, differential methylation testing, region discovery, and annotation for biological interpretation. This skill provides an end-to-end workflow from raw beta-value matrices to publication-ready results.

Core Features & Use Cases

  • QC metrics for per-sample quality assessment and clustering
  • Identification of differential methylation positions (DMPs) with statistical testing and FDR control
  • Identification of differentially methylated regions (DMRs) by aggregating proximate DMPs
  • CpG annotation to genes and regulatory features
  • Publication-quality visualizations (volcano plots, Manhattan plots, heatmaps)
  • Support for two or more sample groups and flexible input configurations

Quick Start

Run the methylation analysis on your beta-value matrix and sample metadata to generate DMP and DMR results, QC metrics, and publication-ready plots.

Frequently Asked Questions about methylation-analysis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I identify differentially methylated positions from Illumina beta-values?▼

Differential methylation analysis of Illumina beta-values identifies DMPs by statistically comparing sample groups with FDR control and delta-beta filtering, outputting ranked tables of differentially methylated positions for biological interpretation.

What is the best way to detect differentially methylated regions in epigenomics data?▼

Detecting differentially methylated regions (DMRs) in epigenomics data is handled by aggregating proximate DMPs into continuous blocks. The skill outputs DMR tables derived from your Illumina beta-value matrix and sample metadata.

Can I generate volcano plots and heatmaps from a DNA methylation beta-value matrix?▼

Yes, you can generate publication-ready visualizations including volcano plots, Manhattan plots, and heatmaps directly from a DNA methylation beta-value matrix. The skill processes sample metadata to produce these plots alongside QC metrics.

Do I need to preprocess IDAT files before running methylation analysis?▼

You need to preprocess raw IDAT files beforehand. The skill requires a pre-computed beta-value matrix and sample metadata as input, rather than raw IDAT files, to perform QC, DMP detection, and DMR annotation.

Does this methylation analysis workflow support more than two sample groups?▼

Yes, the methylation analysis workflow supports two or more sample groups. It requires a beta-value matrix and sample metadata to perform differential methylation testing, CpG annotation, and visualization across flexible input configurations.

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