Agent skill · Data & Analytics

nested-TAD-detection

This skill detects hierarchical (nested) TAD structures from Hi-C contact maps (in .cool or mcool format) using OnTAD, starting from multi-resolution .mcool files. It extracts a user-specified chromosome and resolution, converts the data to a dense matrix, runs OnTAD, and organizes TAD calls and logs for downstream 3D genome analysis.

majiayu000github.com/majiayu000GitHub ↗
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill 31-toolbased-nested-tad-detection-bisnake2001-chromskills-2 --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 10 KB
Bundled scripts: none
Path: skills/ai-ml/31-toolbased-nested-tad-detection-bisnake2001-chromskills-2/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Nested TAD Detection from .mcool Using OnTAD ## Overview This skill performs nested TAD (hierarchical TAD/subTAD) detection from Hi-C data using **OnTAD**, starting from a .mcool, .cool or .hic file. Main steps include: - Refer to the **Inputs & Outputs** section to verify required files and output structure. - Inspect the `.mcool` file to list available resolutions and alway remember to confirm the chromosome name and analysis resolution with the user. - Extract a **balanced or raw dense Hi-C matrix** for a selected chromosome and resolution from the `.mcool` file. - Ensure matrix quality (symmetry, no all-zero rows/columns, reasonable contact decay). - Run **OnTAD** to call TADs and nested TAD structures. - Parse and standardize OnTAD output into BED-like tables and hierarchical annotation files. --- ## When to use this skill Use this skill when you want to **identify TADs and nested sub-TADs** from high- or mid-resolution Hi-C data, especially when your contact maps are stored as **Cooler multi-resolution files (.mcool)** and you need **chromosome- and resolution-specific** OnTAD calls. Typical biological questions / use-cases: - Comparing **TAD hierarchy** between cell types

What's inside
Steps it walks through
  1. Overview
  2. When to use this skill
  3. Inputs & Outputs
  4. Inputs
  5. Outputs
  6. Allowed Tools
  7. Decision Tree
  8. Step 0 — Gather Required Information from the User
  9. Step 1 — Initialize Project
  10. Step 3: Check chromosome length
  11. Step 4: Extract dense matrix from .mcool
  12. Step 5: Run OnTAD
Ships with 1 file
  • metadata.json
Commands it runs
matrices/
nested_TADs/
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About this skill
What does the nested-TAD-detection skill do?

This skill detects hierarchical (nested) TAD structures from Hi-C contact maps (in .cool or mcool format) using OnTAD, starting from multi-resolution .mcool files. It extracts a user-specified chromosome and resolution, converts the data to a dense matrix, runs OnTAD, and organizes TAD calls and logs for downstream 3D genome analysis.

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill 31-toolbased-nested-tad-detection-bisnake2001-chromskills-2 --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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