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# 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
```bash
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
