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

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X-Chromosome Inactivation

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1861))

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.

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Acknowledgments

This work was supported by a RIKEN CDB intramural grant to I.H.

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Authors and Affiliations

  1. Laboratory for Developmental Epigenetics, RIKEN Center for Developmental Biology (CDB) and Center for Biosystems Dynamics Research (BDR), Kobe, Japan

    Hisashi Miura, Rawin Poonperm, Saori Takahashi & Ichiro Hiratani

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  1. Hisashi Miura
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  2. Rawin Poonperm
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  3. Saori Takahashi
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  4. Ichiro Hiratani
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Correspondence to Ichiro Hiratani .

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Editors and Affiliations

  1. Department of Advanced Bioscience, Graduate School of Agriculture, Kindai University, Nara, Japan

    Takashi Sado

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Miura, H., Poonperm, R., Takahashi, S., Hiratani, I. (2018). Practical Analysis of Hi-C Data: Generating A/B Compartment Profiles. In: Sado, T. (eds) X-Chromosome Inactivation. Methods in Molecular Biology, vol 1861. Humana, New York, NY. https://doi.org/10.1007/978-1-4939-8766-5_16

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  • DOI: https://doi.org/10.1007/978-1-4939-8766-5_16

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-4939-8765-8

  • Online ISBN: 978-1-4939-8766-5

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