Binless normalization of Hi-C data provides significant interaction and difference detection independent of resolution

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  • dc.contributor.author Spill, Yannick G.
  • dc.contributor.author Castillo Andreo, David
  • dc.contributor.author Vidal, Enrique
  • dc.contributor.author Marti-Renom, Marc A.
  • dc.date.accessioned 2019-07-19T08:33:44Z
  • dc.date.available 2019-07-19T08:33:44Z
  • dc.date.issued 2019
  • dc.description.abstract Chromosome conformation capture techniques, such as Hi-C, are fundamental in characterizing genome organization. These methods have revealed several genomic features, such as chromatin loops, whose disruption can have dramatic effects in gene regulation. Unfortunately, their detection is difficult; current methods require that the users choose the resolution of interaction maps based on dataset quality and sequencing depth. Here, we introduce Binless, a resolution-agnostic method that adapts to the quality and quantity of available data, to detect both interactions and differences. Binless relies on an alternate representation of Hi-C data, which leads to a more detailed classification of paired-end reads. Using a large-scale benchmark, we demonstrate that Binless is able to call interactions with higher reproducibility than other existing methods. Binless, which is freely available, can thus reliably be used to identify chromatin loops as well as for differential analysis of chromatin interaction maps.
  • dc.description.sponsorship This work has been partially supported by the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013)/ERC Synergy grant agreement 609989 (4Dgenome), the European Union’s Horizon 2020 research and innovation programme (agreement 676556) as well as the Spanish MINECO (BFU2017-85926-P). We acknowledge support of the Spanish Ministry of Economy, Industry and Competitiveness (MEIC) to the EMBL partnership, the Centro de Excelencia Severo Ochoa and the CERCA Programme / Generalitat de Catalunya. We also acknowledge support of the Spanish Ministry of Economy, Industry and Competitiveness (MEIC) through the Instituto de Salud Carlos III, the Generalitat de Catalunya through Departament de Salut and Departament d’Empresa i Coneixement and the Co-financing by the Spanish Ministry of Economy, Industry and Competitiveness (MEIC) with funds from the European Regional Development Fund (ERDF) corresponding to the 2014-2020 Smart Growth Operating Program
  • dc.format.mimetype application/pdf
  • dc.identifier.citation Spill YG, Castillo D, Vidal E, Marti-Renom MA. Binless normalization of Hi-C data provides significant interaction and difference detection independent of resolution. Nat Commun. 2019 Apr 26;10(1):1938. DOI: 10.1038/s41467-019-09907-2
  • dc.identifier.doi http://dx.doi.org/10.1038/s41467-019-09907-2
  • dc.identifier.issn 2041-1723
  • dc.identifier.uri http://hdl.handle.net/10230/42070
  • dc.language.iso eng
  • dc.publisher Nature Research
  • dc.relation.ispartof Nature Communications. 2019 Apr 26;10(1):1938
  • dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/609989
  • dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/676556
  • dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/BFU2017-85926-P
  • dc.rights © Springer Nature Publishing AG. http://dx.doi.org/10.1038/s41467-019-09907-2 This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
  • dc.rights http://creativecommons.org/licenses/by/4.0/
  • dc.rights.accessRights info:eu-repo/semantics/openAccess
  • dc.subject.other Caulobacter crescentus
  • dc.subject.other Cromatina
  • dc.subject.other Gens -- Mapatge
  • dc.subject.other Biologia computacional
  • dc.subject.other ADN
  • dc.subject.other Genomes
  • dc.title Binless normalization of Hi-C data provides significant interaction and difference detection independent of resolution
  • dc.type info:eu-repo/semantics/article
  • dc.type.version info:eu-repo/semantics/publishedVersion

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