Hi-C Visualization - Usage Guide

Hi-C Visualization - Usage Guide

Overview

This skill covers visualizing Hi-C contact matrices, TADs, loops, and other genomic features using matplotlib, cooltools, and HiCExplorer.

Prerequisites

pip install cooler cooltools matplotlib numpy
# For HiCExplorer:
conda install -c bioconda hicexplorer

Quick Start

Tell your AI agent what you want to do:

• "Plot my Hi-C contact matrix"
• "Show Hi-C with TADs and loops"

Example Prompts

Basic Plots

"Plot the contact matrix for chr1:50-60Mb"

"Create a triangle plot of my Hi-C data"

With Annotations

"Plot Hi-C with TAD boundaries"

"Show loops on the contact matrix"

Comparisons

"Compare Hi-C between treatment and control"

"Create a split view of two samples"

What the Agent Will Do

1. Load cooler file
2. Extract matrix for requested region
3. Create matplotlib figure
4. Add annotations (TADs, loops) if requested
5. Save figure

Tips

• Log scale - Use LogNorm for contact matrices
• Color limits - vmin/vmax control dynamic range
• Resolution - Higher resolution = more detail but slower
• Triangle plots - Better for linear arrangement with tracks