Capturing cell type-specific chromatin compartment patterns by applying topic modeling to single-cell Hi-C data.

Single-cell Hi-C (scHi-C) interrogates genome-wide chromatin interaction in individual cells, allowing us to gain insights into 3D genome organization. However, the extremely sparse nature of scHi-C data poses a significant barrier to analysis, limiting our ability to tease out hidden biological inf...

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Autores principales:	Hyeon-Jin Kim, Galip Gürkan Yardımcı, Giancarlo Bonora, Vijay Ramani, Jie Liu, Ruolan Qiu, Choli Lee, Jennifer Hesson, Carol B Ware, Jay Shendure, Zhijun Duan, William Stafford Noble
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2020
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/d087140ff4c3496697afe98471225fab
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id	oai:doaj.org-article:d087140ff4c3496697afe98471225fab
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spelling	oai:doaj.org-article:d087140ff4c3496697afe98471225fab2021-12-02T19:58:15ZCapturing cell type-specific chromatin compartment patterns by applying topic modeling to single-cell Hi-C data.1553-734X1553-735810.1371/journal.pcbi.1008173https://doaj.org/article/d087140ff4c3496697afe98471225fab2020-09-01T00:00:00Zhttps://doi.org/10.1371/journal.pcbi.1008173https://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Single-cell Hi-C (scHi-C) interrogates genome-wide chromatin interaction in individual cells, allowing us to gain insights into 3D genome organization. However, the extremely sparse nature of scHi-C data poses a significant barrier to analysis, limiting our ability to tease out hidden biological information. In this work, we approach this problem by applying topic modeling to scHi-C data. Topic modeling is well-suited for discovering latent topics in a collection of discrete data. For our analysis, we generate nine different single-cell combinatorial indexed Hi-C (sci-Hi-C) libraries from five human cell lines (GM12878, H1Esc, HFF, IMR90, and HAP1), consisting over 19,000 cells. We demonstrate that topic modeling is able to successfully capture cell type differences from sci-Hi-C data in the form of "chromatin topics." We further show enrichment of particular compartment structures associated with locus pairs in these topics.Hyeon-Jin KimGalip Gürkan YardımcıGiancarlo BonoraVijay RamaniJie LiuRuolan QiuCholi LeeJennifer HessonCarol B WareJay ShendureZhijun DuanWilliam Stafford NoblePublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 16, Iss 9, p e1008173 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Hyeon-Jin Kim Galip Gürkan Yardımcı Giancarlo Bonora Vijay Ramani Jie Liu Ruolan Qiu Choli Lee Jennifer Hesson Carol B Ware Jay Shendure Zhijun Duan William Stafford Noble Capturing cell type-specific chromatin compartment patterns by applying topic modeling to single-cell Hi-C data.
description	Single-cell Hi-C (scHi-C) interrogates genome-wide chromatin interaction in individual cells, allowing us to gain insights into 3D genome organization. However, the extremely sparse nature of scHi-C data poses a significant barrier to analysis, limiting our ability to tease out hidden biological information. In this work, we approach this problem by applying topic modeling to scHi-C data. Topic modeling is well-suited for discovering latent topics in a collection of discrete data. For our analysis, we generate nine different single-cell combinatorial indexed Hi-C (sci-Hi-C) libraries from five human cell lines (GM12878, H1Esc, HFF, IMR90, and HAP1), consisting over 19,000 cells. We demonstrate that topic modeling is able to successfully capture cell type differences from sci-Hi-C data in the form of "chromatin topics." We further show enrichment of particular compartment structures associated with locus pairs in these topics.
format	article
author	Hyeon-Jin Kim Galip Gürkan Yardımcı Giancarlo Bonora Vijay Ramani Jie Liu Ruolan Qiu Choli Lee Jennifer Hesson Carol B Ware Jay Shendure Zhijun Duan William Stafford Noble
author_facet	Hyeon-Jin Kim Galip Gürkan Yardımcı Giancarlo Bonora Vijay Ramani Jie Liu Ruolan Qiu Choli Lee Jennifer Hesson Carol B Ware Jay Shendure Zhijun Duan William Stafford Noble
author_sort	Hyeon-Jin Kim
title	Capturing cell type-specific chromatin compartment patterns by applying topic modeling to single-cell Hi-C data.
title_short	Capturing cell type-specific chromatin compartment patterns by applying topic modeling to single-cell Hi-C data.
title_full	Capturing cell type-specific chromatin compartment patterns by applying topic modeling to single-cell Hi-C data.
title_fullStr	Capturing cell type-specific chromatin compartment patterns by applying topic modeling to single-cell Hi-C data.
title_full_unstemmed	Capturing cell type-specific chromatin compartment patterns by applying topic modeling to single-cell Hi-C data.
title_sort	capturing cell type-specific chromatin compartment patterns by applying topic modeling to single-cell hi-c data.
publisher	Public Library of Science (PLoS)
publishDate	2020
url	https://doaj.org/article/d087140ff4c3496697afe98471225fab
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Capturing cell type-specific chromatin compartment patterns by applying topic modeling to single-cell Hi-C data.

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