Methylation analysis

Methylation Analysis

Version Compatibility

Reference examples assume recent stable releases of the preferred tools, especially Bismark-like and the other tools listed below.

Before using code or command patterns, verify installed versions match the environment:

• Python: python -c "import <module>; print(<module>.__version__)"
• CLI: <tool> --version
• If signatures differ, inspect the installed help or API and adapt the pattern instead of retrying unchanged.

Overview

Workflow for methylation alignment or calling, DMR analysis, methylation QC, and locus-level interpretation.

When To Use This Skill

• use when the task is DNA methylation calling or differential methylation
• use when bisulfite or long-read methylation data must be summarized at loci or regions
• use when methylation QC and DMR export are required

Quick Route

• If the input is raw or minimally processed data, start with validation and QC before any modeling.
• If the input is already processed, skip directly to the first workflow step that matches the user goal.
• If the user asks for a biological conclusion, always produce at least one QC or confidence artifact alongside the final result.

Progressive Disclosure

• Read references/technical_reference.md when you need deeper tool-selection rules, environment adaptation notes, or extra validation guidance.
• Keep SKILL.md as the main execution path and load the reference file only when the task or failure mode needs the extra detail.

Default Rules

• Prefer Python-first workflows unless the task explicitly requires something else.
• Keep intermediate and final outputs separated.
• Record software versions, reference builds, and key parameters when they affect interpretation.
• Favor reproducible tables and figures over one-off interactive-only outputs.

Expected Inputs

• methylation-aware sequencing reads
• reference genome
• sample metadata

Expected Outputs

• methylation calls
• DMR tables
• sample and locus QC plots

Preferred Tools

• Bismark-like workflows
• pandas
• matplotlib
• seaborn

Starter Pattern

Preferred starting point: Bismark-like
Inputs: methylation-aware sequencing reads, reference genome, sample metadata
Outputs: methylation calls, DMR tables, sample and locus QC plots

Workflow

1. Check assay-specific preprocessing

Use the correct alignment or calling path for bisulfite versus direct methylation detection.

2. Summarize methylation levels

Aggregate calls at CpG, region, or feature level appropriate to the study question.

3. Run differential analysis

Test differences using replicate-aware region-based methods when possible.

4. Inspect biological context

Annotate DMRs to promoters, enhancers, or other regions before interpretation.

5. Export report-ready outputs

Save calls, DMR tables, and locus-level example plots.

Output Artifacts

• Recommended output layout:
  • results/ for final tables and serialized objects
  • figures/ for plots and static visual exports
  • qc/ for checks that justify downstream interpretation
• Minimum expected outputs for this skill:
• methylation calls
• DMR tables
• sample and locus QC plots

Quality Review

• Confirm identifiers and metadata join correctly before modeling or summarizing.
• Generate at least one QC artifact before final biological interpretation.
• Keep raw or minimally processed inputs separate from transformed outputs.
• Check assay-specific QC such as enrichment quality, coverage behavior, or replicate consistency.
• Verify genome build, interval coordinates, and annotation compatibility.

Anti-Patterns

• mixing assay types without documenting the calling method
• reporting regional changes without effect direction and coverage context
• ignoring low-coverage loci during interpretation

Related Skills

• ATAC Seq
• ChIP Seq
• Epitranscriptomics
• Hi-C And 3D Genomics

Optional Supplements

• None required for the first pass.