SuperTAD: robust detection of hierarchical topologically associated domains with optimized structural information

Topologically associating domains (TADs) are the organizational units of chromosome structures. TADs can contain TADs, thus forming a hierarchy. TAD hierarchies can be inferred from Hi-C data through coding trees. However, the current method for computing coding trees is not optimal. In this paper,...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhang, Yu Wei, Wang, Meng Bo, Li, Shuai Cheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Method
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7831269/
https://www.ncbi.nlm.nih.gov/pubmed/33494803
http://dx.doi.org/10.1186/s13059-020-02234-6
_version_ 1783641600182714368
author Zhang, Yu Wei
Wang, Meng Bo
Li, Shuai Cheng
author_facet Zhang, Yu Wei
Wang, Meng Bo
Li, Shuai Cheng
author_sort Zhang, Yu Wei
collection PubMed
description Topologically associating domains (TADs) are the organizational units of chromosome structures. TADs can contain TADs, thus forming a hierarchy. TAD hierarchies can be inferred from Hi-C data through coding trees. However, the current method for computing coding trees is not optimal. In this paper, we propose optimal algorithms for this computation. In comparison with seven state-of-art methods using two public datasets, from GM12878 and IMR90 cells, SuperTAD shows a significant enrichment of structural proteins around detected boundaries and histone modifications within TADs and displays a high consistency between various resolutions of identical Hi-C matrices. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1186/s13059-020-02234-6).
format Online
Article
Text
id pubmed-7831269
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-78312692021-01-26 SuperTAD: robust detection of hierarchical topologically associated domains with optimized structural information Zhang, Yu Wei Wang, Meng Bo Li, Shuai Cheng Genome Biol Method Topologically associating domains (TADs) are the organizational units of chromosome structures. TADs can contain TADs, thus forming a hierarchy. TAD hierarchies can be inferred from Hi-C data through coding trees. However, the current method for computing coding trees is not optimal. In this paper, we propose optimal algorithms for this computation. In comparison with seven state-of-art methods using two public datasets, from GM12878 and IMR90 cells, SuperTAD shows a significant enrichment of structural proteins around detected boundaries and histone modifications within TADs and displays a high consistency between various resolutions of identical Hi-C matrices. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1186/s13059-020-02234-6). BioMed Central 2021-01-25 /pmc/articles/PMC7831269/ /pubmed/33494803 http://dx.doi.org/10.1186/s13059-020-02234-6 Text en © The Author(s) 2021 Open Access 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Method
Zhang, Yu Wei
Wang, Meng Bo
Li, Shuai Cheng
SuperTAD: robust detection of hierarchical topologically associated domains with optimized structural information
title SuperTAD: robust detection of hierarchical topologically associated domains with optimized structural information
title_full SuperTAD: robust detection of hierarchical topologically associated domains with optimized structural information
title_fullStr SuperTAD: robust detection of hierarchical topologically associated domains with optimized structural information
title_full_unstemmed SuperTAD: robust detection of hierarchical topologically associated domains with optimized structural information
title_short SuperTAD: robust detection of hierarchical topologically associated domains with optimized structural information
title_sort supertad: robust detection of hierarchical topologically associated domains with optimized structural information
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7831269/
https://www.ncbi.nlm.nih.gov/pubmed/33494803
http://dx.doi.org/10.1186/s13059-020-02234-6
work_keys_str_mv AT zhangyuwei supertadrobustdetectionofhierarchicaltopologicallyassociateddomainswithoptimizedstructuralinformation
AT wangmengbo supertadrobustdetectionofhierarchicaltopologicallyassociateddomainswithoptimizedstructuralinformation
AT lishuaicheng supertadrobustdetectionofhierarchicaltopologicallyassociateddomainswithoptimizedstructuralinformation

Ejemplares similares