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Hi-C Data Analysis pp 61–95Cite as

Methods for the Differential Analysis of Hi-C Data

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Part of the book series: Methods in Molecular Biology ((MIMB,volume 2301))

Abstract

The 3D organization of chromatin within the nucleus enables dynamic regulation and cell type-specific transcription of the genome. This is true at multiple levels of resolution: on a large scale, with chromosomes occupying distinct volumes (chromosome territories); at the level of individual chromatin fibers, which are organized into compartmentalized domains (e.g., Topologically Associating Domains—TADs), and at the level of short-range chromatin interactions between functional elements of the genome (e.g., enhancer-promoter loops).

The widespread availability of Chromosome Conformation Capture (3C)-based high-throughput techniques has been instrumental in advancing our knowledge of chromatin nuclear organization. In particular, Hi-C has the potential to achieve the most comprehensive characterization of chromatin 3D interactions, as it is theoretically able to detect any pair of restriction fragments connected as a result of ligation by proximity.

This chapter will illustrate how to compare the chromatin interactome in different experimental conditions, starting from pre-computed Hi-C contact matrices, how to visualize the results, and how to correlate the observed variations in chromatin interaction strength with changes in gene expression.

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Acknowledgments

This work was supported by the American Heart Association Postdoctoral Fellowship 19POST34450187 to C.N. I thank Silvio Bicciato for providing the computational resources to run the analyses described in the chapter and Silvio Bicciato, Pier Lorenzo Puri, and Luca Caputo for critical feedback on the manuscript. Last but not least, I want to express my gratitude to my parents, for supporting me in everything I do.

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Authors and Affiliations

  1. Development, Aging and Regeneration Program, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, USA

    Chiara Nicoletti

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  1. Chiara Nicoletti
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Correspondence to Chiara Nicoletti .

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Editors and Affiliations

  1. Department of Life Sciences, University of Modena and Reggio Emilia, Modena, Italy

    Silvio Bicciato

  2. IFOM, The FIRC Institute of Molecular Oncology, Milan, Italy

    Francesco Ferrari

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Nicoletti, C. (2022). Methods for the Differential Analysis of Hi-C Data. In: Bicciato, S., Ferrari, F. (eds) Hi-C Data Analysis. Methods in Molecular Biology, vol 2301. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1390-0_4

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  • DOI: https://doi.org/10.1007/978-1-0716-1390-0_4

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