Practical Analysis of Hi-C Data: Generating A/B Compartment Profiles

Methods Mol Biol. 2018:1861:221-245. doi: 10.1007/978-1-4939-8766-5_16.

Abstract

Recent advances in next-generation sequencing (NGS) and chromosome conformation capture (3C) analysis have led to the development of Hi-C, a genome-wide version of the 3C method. Hi-C has identified new levels of chromosome organization such as A/B compartments, topologically associating domains (TADs) as well as large megadomains on the inactive X chromosome, while allowing the identification of chromatin loops at the genome scale. Despite its powerfulness, Hi-C data analysis is much more involved compared to conventional NGS applications such as RNA-seq or ChIP-seq and requires many more steps. This presents a significant hurdle for those who wish to implement Hi-C technology into their laboratory. On the other hand, genomics data repository sites sometimes contain processed Hi-C data sets, allowing researchers to perform further analysis without the need for high-spec workstations and servers. In this chapter, we provide a detailed description on how to calculate A/B compartment profiles from processed Hi-C data on the autosomes and the active/inactive X chromosomes.

Keywords: 3D genome organization; A/B compartments; Bioinformatics; Epigenetics; Hi-C contact map; Inactive X chromosome.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Chromatin / metabolism
  • Chromatin / ultrastructure*
  • Computational Biology
  • DNA / chemistry
  • DNA / metabolism
  • Genomics / methods*
  • High-Throughput Nucleotide Sequencing / methods*
  • Humans
  • Mice
  • Nucleic Acid Conformation*
  • Sequence Analysis, DNA / methods
  • Software*

Substances

  • Chromatin
  • DNA