nested-tad-detection

name	nested-TAD-detection
description	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.

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.

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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 (e.g., GM12878 vs K562) or conditions (control vs treated).
• Investigating whether inner subTADs are enriched for active regulatory elements, specific histone marks, or gene expression.
• Studying boundary usage, boundary sharing, or hierarchical TAD levels around key loci (e.g., HOX clusters, oncogenes).
• Integrating nested TAD structure with ChIP-seq, ATAC-seq, or WGBS to understand spatial regulatory architecture.

Data quality & replication assumptions:

• Hi-C experiments should have sufficient depth for the target resolution (e.g., ≥5–10 kb typically requires deep sequencing).
• Preferably, use biological replicates per condition and call TADs on either:
  • individual replicate matrices (and then merge/consensus), or
  • replicate-merged matrices (if justified).
• The .mcool should be properly normalized or at least QC’d (ICE/balanced weights available if using --balanced).

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Inputs & Outputs

Inputs

Required core inputs:

• Hi-C matrix file
  • Multi-resolution Cooler file (.mcool), e.g.:
    • sample.mcool
  • Or one-resolution Cooler file (.cool), e.g.:
    • sample.cool
  • Or Hi-C file (.hic), e.g.:
    • sample.hic
• User-supplied parameters (must come from user feedback)
  • Chromosome name: e.g., chr1, chr2, chrX
  • Resolution of interest: e.g., 10000, 25000, 40000 (in bp)
  • Chromosome length: e.g., 133275309
• Software and environment
  • cooler command-line utilities (or Python cooler module) available in $PATH or environment.
  • OnTAD installed and callable (e.g., OnTAD or OnTAD_linux command).
  • python (3.x) and basic scientific Python stack if using Python-based extraction.

Optional entry point:

• Precomputed dense Hi-C matrix (OnTAD-ready)
  • Plain text dense square matrix (no header), e.g. proj_dir/matrices/chr17_25kb_dense.matrix.
  • If this is already present, you may skip the .mcool → dense matrix conversion and jump directly to OnTAD.

Operational rules for missing inputs:

• If .mcool or .cool or .hic file is missing:
  "sample.mcool not available, provide required files or skip and proceed ?"
• If chromosome list not specified:
  Ask the user explicitly rather than assuming default.
• If OnTAD executable is not found:
  Ask user to install/locate OnTAD before proceeding.

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Outputs

Default output directory structure:

${sample}_nested_TAD_detection/
    matrices/
        ${chromosome}_${resolution}_dense.txt
        ${chromosome}_${resolution}_dense.log
    nested_TADs/
        ${chromosome}_${resolution}_OnTAD.tad
        ${chromosome}_${resolution}_OnTAD.bed
        ${chromosome}_${resolution}_OnTAD.log

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Allowed Tools

When using this skill, you should restrict yourself to the following MCP tools from server cooler-tools, cooltools-tools, plot-hic-tools, project-init-tools:

• mcp__project-init-tools__project_init
• mcp__cooler-tools__list_mcool_resolutions
• mcp__cooler-tools__harmonize_chrom_names
• mcp__cooler-tools__dump_chroms
• mcp__cooler-tools__dump_dense_matrix
• mcp__OnTAD-tools__run_ontad

Do NOT fall back to:

• raw shell commands (OnTAD, etc.)
• ad-hoc Python snippets (e.g. importing cooler, bioframe, matplotlib manually in the reply).

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Decision Tree

Step 0 — Gather Required Information from the User

Before calling any tool, ask the user:

1. Sample name (sample): used as prefix and for the output directory ${sample}_nested_TAD_detection.

2. Genome assembly (genome): e.g. hg38, mm10, danRer11.

   • Never guess or auto-detect.

3. Hi-C matrix path/URI (mcool_uri):

   • path/to/sample.mcool::/resolutions/25000 (.mcool file with resolution specified)
   • or .cool file path
   • or .hic file path

4. Resolution (resolution): default 25000 (100 kb).

   • If user does not specify, use 25000 as default.
   • Must be the same as the resolution used for ${mcool_uri}

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Step 1 — Initialize Project

1. Make director for this project:

Call:

• mcp__project-init-tools__project_init

with:

• sample: the user-provided sample name
• task: hic_matrix_qc

The tool will:

• Create ${sample}_nested_TAD_detection directory.
• Return the full path of the ${sample}_nested_TAD_detection directory, which will be used as ${proj_dir}.

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2. If the user provides a .hic file, convert it to .mcool file using mcp__HiCExplorer-tools__hic_to_mcool tool:

Call:

• mcp__HiCExplorer-tools__hic_to_mcool

with:

• input_hic: the user-provided path (e.g. input.hic)
• sample: the user-provided sample name
• proj_dir: directory to save the view file. In this skill, it is the full path of the ${sample}_nested_TAD_detection directory returned by mcp__project-init-tools__project_init.

The tool will:

• Convert the .hic file to .mcool file.
• Return the path of the .mcool file.

If the conversion is successful, update ${mcool_uri} to the path of the .mcool file.

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Step 2: List Available Resolutions in the .mcool file & Modify the Chromosome Names if Necessary

1. Check the resolutions in mcool_uri:

Call:

• mcp__cooler-tools__list_mcool_resolutions

with:

• mcool_path: the user-provided path (e.g. input.mcool) without resolution specified.

The tool will:

• List all resolutions in the .mcool file.
• Return the resolutions as a list.

If the user defined or default ${resolution} is not found in the list, ask the user to specify the resolution again. Else, use ${resolution} for the following steps.

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2. Check if the chromosome names in the .mcool file are started with "chr", and if not, modify them to start with "chr":

Call:

• mcp__cooler-tools__harmonize_chrom_names

with:

• sample: the user-provided sample name
• proj_dir: directory to save the expected-cis and eigs-cis files. In this skill, it is the full path of the ${sample}_Compartments_calling directory returned by mcp__project-init-tools__project_init
• mcool_uri: cooler URI with resolution specified, e.g. input.mcool::/resolutions/${resolution}
• resolution: ${resolution} must be the same as the resolution used for ${mcool_uri} and must be an integer

The tool will:

• Check if the chromosome names in the .mcool file.
• If not, harmonize the chromosome names in the .mcool file.
• If the chromosome names are modified, return the path of the modified .mcool file under ${proj_dir}/ directory

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Step 3: Check chromosome length

Call:

• mcp__cooler-tools__dump_chroms

with:

• mcool_uri: cooler URI with resolution specified, e.g. input.mcool::/resolutions/${resolution}
• resolution: ${resolution} must be the same as the resolution used for ${mcool_uri} and must be an integer

The tool will:

• Return the chromosome name and length as a table.

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Step 4: Extract dense matrix from .mcool

Call:

• mcp__cooler-tools__dump_dense_matrix

with:

• sample: the user-provided sample name
• proj_dir: directory to save the view file. In this skill, it is the full path of the ${sample}_nested_TAD_detection directory returned by mcp__project-init-tools__project_init.
• mcool_uri: cooler URI with resolution specified, e.g. input.mcool::/resolutions/${resolution}
• resolution: ${resolution} must be the same as the resolution used for ${mcool_uri} and must be an integer
• chrom: the user-provided chromosome name (e.g. chr17)
• balanced: whether to use balanced matrix (default: True)

The tool will:

• Extract the dense matrix from the .mcool file.
• Return the path of the dense matrix file.

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Step 5: Run OnTAD

Call:

• mcp__OnTAD-tools__run_ontad

with:

• sample: the user-provided sample name
• proj_dir: directory to save the view file. In this skill, it is the full path of the ${sample}_nested_TAD_detection directory returned by mcp__project-init-tools__project_init.
• dense_matrix: the path to the dense matrix file (e.g. ${proj_dir}/matrices/chr17_25kb_dense.matrix)
• chrom: the user-provided chromosome name (e.g. chr17)
• chrom_length: the corresponding chromosome length (e.g. 83257441) returned by mcp__cooler-tools__dump_chroms tool.
• resolution: the user-provided resolution (e.g. 25000)
• penalty: the penalty parameter for OnTAD (e.g. 0.1)
• maxsz: the maximum TAD size (in bins) (e.g. 200)

The tool will:

• Run OnTAD to call TADs and nested TAD structures.
• Return the path of the OnTAD output file (.tad, .bed, .log).