Decoding topologically associating domains with ultra-low resolution Hi-C data by graph structural entropy

Accurate detection of TADs requires ultra-deep sequencing and sophisticated normalisation procedures, which limits the analysis of Hi-C data. Here the authors develop a normalisation-free method to decode the domains of chromosomes (deDoc) that utilizes structural entropy to predict TADs with ultra-...

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Main Authors:	Angsheng Li, Xianchen Yin, Bingxiang Xu, Danyang Wang, Jimin Han, Yi Wei, Yun Deng, Ying Xiong, Zhihua Zhang
Format:	Article
Language:	English
Published:	Nature Publishing Group 2018-08-01
Series:	Nature Communications
Online Access:	https://doi.org/10.1038/s41467-018-05691-7

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spelling	doaj-46fdb2762a7445d7993295e0787688652021-05-11T09:41:49ZengNature Publishing GroupNature Communications2041-17232018-08-019111210.1038/s41467-018-05691-7Decoding topologically associating domains with ultra-low resolution Hi-C data by graph structural entropyAngsheng Li0Xianchen Yin1Bingxiang Xu2Danyang Wang3Jimin Han4Yi Wei5Yun Deng6Ying Xiong7Zhihua Zhang8State Key Laboratory of Software Development Environment, School of Computer Science, Beihang UniversityState Key Laboratory of Computer Science, Institute of Software, Chinese Academy of SciencesCAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of SciencesCAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of SciencesSchool of Computer Science, University of Chinese Academy of SciencesSchool of Mathematics, University of Chinese Academy of SciencesSchool of Life Science, University of Chinese Academy of SciencesSchool of Physics, University of Chinese Academy of SciencesCAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of SciencesAccurate detection of TADs requires ultra-deep sequencing and sophisticated normalisation procedures, which limits the analysis of Hi-C data. Here the authors develop a normalisation-free method to decode the domains of chromosomes (deDoc) that utilizes structural entropy to predict TADs with ultra-low sequencing data.https://doi.org/10.1038/s41467-018-05691-7
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Angsheng Li Xianchen Yin Bingxiang Xu Danyang Wang Jimin Han Yi Wei Yun Deng Ying Xiong Zhihua Zhang
spellingShingle	Angsheng Li Xianchen Yin Bingxiang Xu Danyang Wang Jimin Han Yi Wei Yun Deng Ying Xiong Zhihua Zhang Decoding topologically associating domains with ultra-low resolution Hi-C data by graph structural entropy Nature Communications
author_facet	Angsheng Li Xianchen Yin Bingxiang Xu Danyang Wang Jimin Han Yi Wei Yun Deng Ying Xiong Zhihua Zhang
author_sort	Angsheng Li
title	Decoding topologically associating domains with ultra-low resolution Hi-C data by graph structural entropy
title_short	Decoding topologically associating domains with ultra-low resolution Hi-C data by graph structural entropy
title_full	Decoding topologically associating domains with ultra-low resolution Hi-C data by graph structural entropy
title_fullStr	Decoding topologically associating domains with ultra-low resolution Hi-C data by graph structural entropy
title_full_unstemmed	Decoding topologically associating domains with ultra-low resolution Hi-C data by graph structural entropy
title_sort	decoding topologically associating domains with ultra-low resolution hi-c data by graph structural entropy
publisher	Nature Publishing Group
series	Nature Communications
issn	2041-1723
publishDate	2018-08-01
description	Accurate detection of TADs requires ultra-deep sequencing and sophisticated normalisation procedures, which limits the analysis of Hi-C data. Here the authors develop a normalisation-free method to decode the domains of chromosomes (deDoc) that utilizes structural entropy to predict TADs with ultra-low sequencing data.
url	https://doi.org/10.1038/s41467-018-05691-7
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Decoding topologically associating domains with ultra-low resolution Hi-C data by graph structural entropy

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