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DOI: 10.4230/LIPIcs.WABI.2019.11

Inferring Diploid 3D Chromatin Structures from Hi-C Data

Authors: Alexandra Gesine Cauer, Gürkan Yardımcı, Jean-Philippe Vert, Nelle Varoquaux, and William Stafford Noble

Published in: LIPIcs, Volume 143, 19th International Workshop on Algorithms in Bioinformatics (WABI 2019)

Abstract

The 3D organization of the genome plays a key role in many cellular processes, such as gene regulation, differentiation, and replication. Assays like Hi-C measure DNA-DNA contacts in a high-throughput fashion, and inferring accurate 3D models of chromosomes can yield insights hidden in the raw data. For example, structural inference can account for noise in the data, disambiguate the distinct structures of homologous chromosomes, orient genomic regions relative to nuclear landmarks, and serve as a framework for integrating other data types. Although many methods exist to infer the 3D structure of haploid genomes, inferring a diploid structure from Hi-C data is still an open problem. Indeed, the diploid case is very challenging, because Hi-C data typically does not distinguish between homologous chromosomes. We propose a method to infer 3D diploid genomes from Hi-C data. We demonstrate the accuracy of the method on simulated data, and we also use the method to infer 3D structures for mouse chromosome X, confirming that the active homolog exhibits a bipartite structure, whereas the active homolog does not.

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Alexandra Gesine Cauer, Gürkan Yardımcı, Jean-Philippe Vert, Nelle Varoquaux, and William Stafford Noble. Inferring Diploid 3D Chromatin Structures from Hi-C Data. In 19th International Workshop on Algorithms in Bioinformatics (WABI 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 143, pp. 11:1-11:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{cauer_et_al:LIPIcs.WABI.2019.11,
  author =	{Cauer, Alexandra Gesine and Yard{\i}mc{\i}, G\"{u}rkan and Vert, Jean-Philippe and Varoquaux, Nelle and Noble, William Stafford},
  title =	{{Inferring Diploid 3D Chromatin Structures from Hi-C Data}},
  booktitle =	{19th International Workshop on Algorithms in Bioinformatics (WABI 2019)},
  pages =	{11:1--11:13},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-123-8},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{143},
  editor =	{Huber, Katharina T. and Gusfield, Dan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2019.11},
  URN =		{urn:nbn:de:0030-drops-110418},
  doi =		{10.4230/LIPIcs.WABI.2019.11},
  annote =	{Keywords: Genome 3D architecture, chromatin structure, Hi-C, 3D modeling}
}

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Inferring Diploid 3D Chromatin Structures from Hi-C Data

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