local-methylation-profile
This skill analyzes the local DNA methylation profiles around target genomic regions provide by user. Use this skill when you want to vasulize the average methylation profile around target regions (e.g. TSS, CTCF peak or other target regions).
Best use case
local-methylation-profile is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
This skill analyzes the local DNA methylation profiles around target genomic regions provide by user. Use this skill when you want to vasulize the average methylation profile around target regions (e.g. TSS, CTCF peak or other target regions).
Teams using local-methylation-profile should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/22-local-methylation-profile/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How local-methylation-profile Compares
| Feature / Agent | local-methylation-profile | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
This skill analyzes the local DNA methylation profiles around target genomic regions provide by user. Use this skill when you want to vasulize the average methylation profile around target regions (e.g. TSS, CTCF peak or other target regions).
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Local Methylation Profile Analysis
## Overview
- **Always prompt user** for which columns in the BED files are methylation fraction/percent. Never decide by yourself.
- Generat profile: Bin methylation around regions (±flank, fixed bin size), aggregate mean±SE.
- Visualize: Plot mean profile with ribbon and center line.
---
## Inputs & Outputs
### Inputs
```bash
methylation.bed
target_regions.bed
```
### Outputs
```bash
local_methyl_profile/
stats/
CpG_around_target.tsv
plots/
CpG_around_target.pdf
temp/
... # other temp file generated
```
---
## Decision Tree
### Step 1: Preprocess input → 5-column BED (for methylKit), and 3-column BED (for target regions)
```bash
awk -F'\t' 'BEGIN {OFS="\t"} {print $1, $2, $3, $<i_methylation>}, $<i_coverage>}' methylation.bed # n is provide by user, *100 if is fraction
awk -F'\t' 'BEGIN {OFS="\t"} {print $1, $2, $3}' target_regions.bed
```
---
### Step 2: Build methylation profiles around regions
Call:
- `mcp__methyl-tools__build_local_methylation_profile`
with:
- `methyl_bed_path`: 5-column BED-like file from preprocess_methylation.
- `regions_bed_path`: 3-column BED-like file from preprocess_regions.
- `output_profile_tsv_path`: path for aggregated profile table (TSV).
- `flank_size`: flank size in bp around region center (default 2000).
- `bin_size`: bin size in bp (default 50).
- `min_coverage`: minimum coverage threshold for CpGs (default 10).
---
### Step 3: Visualization
Call:
- `mcp__methyl-tools__plot_profile`
with:
- `profile_tsv_path`: TSV from build_methylation_profile.
- `output_plot_path`: output figure path (PNG/PDF; format inferred from extension).
- `title`: plot title (optional).
---
## Parameter Guidelines
| Context | Flank | Bin | Min cov |
|-----------|-------|------|---------|
| TF peaks | ±2 kb | 50bp | 10x |
| Promoters | ±1 kb | 50bp | 10x |
| Enhancers | ±5 kb | 100bp| 5x |
| Motifs | ±0.5kb| 10–20| 10x |
## Notes
- Snippets are *usage hints* and must be adapted to your paths and column indices.Related Skills
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