Analysis of Chromatin Structure Using Network Approaches: A Step-by-Step Guide

Chromosome Conformation Capture assays, such as High-throughput Chromosome Conformation Capture (Hi-C) and Promoter Capture Hi-C (PCHi-C), have transformed our comprehension of 3D genome organization in the nucleus. However, these techniques require computational expertise to analyze the data and extract interpretable biological signals, and a number of dedicated tools have therefore been developed. In this chapter, we present a step-by-step guide to ChAseR, an R package to analyze chromatin architecture using network-based approaches. Chromatin contact data are represented as a graph in which nodes correspond to genomic fragments and edges to physical interactions. ChAseR can add diverse genomic and epigenomic features to nodes (e.g., histone marks from ChIP-seq, chromatin accessibility from ATAC-seq, or gene expression from RNA-seq). ChAseR uses chromatin assortativity (ChAs), which provides information on the 3D organization of the nucleus by quantifying the 3D clustering of distinct genomic and epigenomic features. We illustrate the workflow on a promoter-centered chromatin network derived from human monocytes.