# Topological Data Analysis of Single-cell Hi-C Contact Maps

## TL;DR

This paper applies advanced topological data analysis techniques to single-cell Hi-C contact maps, enabling formal detection and quantification of biological topological structures within the data.

## Contribution

It extends the Mapper algorithm to analyze biological datasets, providing a statistical framework for identifying topological features in contact maps.

## Key findings

- Successful extension of Mapper for biological data analysis
- Quantitative methods for topological feature detection in contact maps
- Enhanced understanding of biological structures through topology

## Abstract

In this article, we show how the recent statistical techniques developed in Topological Data Analysis for the Mapper algorithm can be extended and leveraged to formally define and statistically quantify the presence of topological structures coming from biological phenomena in datasets of CCC contact maps.