DeTOKI identifies and characterizes the dynamics of chromatin TAD-like domains in a single cell

Li, Xiao; Zeng, Guangjie; Li, Angsheng; Zhang, Zhihua

doi:10.1186/s13059-021-02435-7

Cited by 23 publications

(38 citation statements)

References 69 publications

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“…Next, we sought to assess the performance of deDoc2 by comparing it with seven state-of-the-art algorithms, i.e., Insulation score (IS) 46 , deDoc 33 , SpectralTAD 35 , GRiNCH 47 , deTOKI 42 , scHiCluster 48 and Higashi 49 . These seven methods can be grouped into those mostly designed for sparseness (SpectralTAD and GRiNCH) or single cell (deTOKI, scHiCluster and Higashi).…”

Section: Resultsmentioning

confidence: 99%

“…2i, 2j). We simulated Hi-C data from a 3D chromosome structure ensemble containing about 100 single cells 42…”

Section: Resultsmentioning

confidence: 99%

“…Next, we compared predictions among deDoc2, deDoc 33 , SpectralTAD 35 , GRiNCH 47 , deTOKI 42 , scHiCluster 48 and Higashi 49 , using three representative experimental scHi-C datasets (hereinafter denoted as Tan’s 53 , Nagano’s 54 , and Lee’s 55 ) (Supplementary Table 1-3). We found the predictions of deDoc2, in most cases, to be among the top category.…”

Section: Resultsmentioning

confidence: 99%

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DeDoc2 identifies and characterizes the hierarchy and dynamics of chromatin TAD-like domains in the single cells

Zeng

Wang

et al. 2022

Preprint

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Topologically associating domains (TAD) are functional chromatin units with hierarchical structure. However, the existence, prevalence and dynamics of such hierarchy in single cells remain unexplored. Here, we report a new generation TAD-like domain (TLD) detection algorithm, named deDoc2, to decode the hierarchy of TLDs in single cells. With dynamic programming, deDoc2 seeks genome partitions with global minimal structure entropy for both whole and local contact matrix. Compared to state-of-the-art tools, deDoc2 can uniquely identify the hierarchy of TLDs in single cells, in addition to outperforming its competitors. By applying deDoc2, we showed that the hierarchy of TLDs in single cells is highly dynamic during cell cycle, as well as among human brain cortex cells, and that it is associated with cellular identity and functions. Thus, our results demonstrated the abundance of information potentially encoded by TLD hierarchy for functional regulation. The deDoc2 can be freely accessed at https://github.com/zengguangjie/deDoc2.

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Section: Resultsmentioning

confidence: 99%

“…2i, 2j). We simulated Hi-C data from a 3D chromosome structure ensemble containing about 100 single cells 42…”

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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DeDoc2 identifies and characterizes the hierarchy and dynamics of chromatin TAD-like domains in the single cells

Zeng

Wang

et al. 2022

Preprint

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“…Quality control of sequencing data is crucial to avoid technical artifacts. Despite of these challenges, new sets of computational methods have been developed for processing scHi-C data to reconstruct single-cell 3D chromatin structures [107] , [108] , [109] , to impute the chromosome contact matrices [110] , [111] , [112] , to identify TAD-like domains [113] , to classify single cells [114] , to identify chromatin loops [115] , and to provide toolbox of scHi-C [116] .…”

Section: Advances In Schi-c Computational Analysesmentioning

confidence: 99%

Mapping nucleosome and chromatin architectures: A survey of computational methods

Fang

Wang²,

Liu³

et al. 2022

Computational and Structural Biotechnology Journal

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“…1b and c HiCS shows superior performance. We benchmark the performance of HiCS for domain detection against two methods: one is the commonly used method for bulk data, insulation score (IS) [15], and another is a single-cell TAD detection method, deTOKI [16]. We apply these methods to the preprocessed single-cell Hi-C data generated from mESCs [17].…”

Section: Overview Of Hicsmentioning

confidence: 99%

Deciphering Hierarchical Chromatin Domains and Preference of Genomic Position Forming Boundaries in Single Mouse Embryonic Stem Cells

Zhang

Gao

et al. 2022

Preprint

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Recent developments in the three-dimensional (3D) genome have revealed chromatin organization with hierarchical architectures at different genomic scales. Transcriptional regulators and their specific interactions implicate gene expression programs by complex chromatin structures. The exploration of single-cell 3D genome maps reveals that chromatin domains are indeed physical structures presenting in single cells and domain boundaries vary from cell to cell. However, the formation mechanism and functional implication of hierarchical chromatin structures in single cells is still blurry. To this end, we first develop a hierarchical chromatin structure identification algorithm (named as HiCS) from individual single-cell Hi-C maps, with superior performance in both accuracy and efficiency. The enrichment of hundreds of regulatory factors in domain boundaries suggests that in addition to the CTCF-cohesin complex, Polycomb, TrxG, pluripotent protein families and other multiple factors also contribute to shaping chromatin landscapes in single embryonic stem cells. We further decipher the preference of genomic positions-function relationship by grouping and annotating chromatin landscape clusters with different types of regulatory factors, and the relationship corresponds to precisely the largest five types of retrotransposons. Our results suggest that multiple types of regulatory factors interplaying with each other in specific genomic positions may navigate the preference of genomic positions, and then shape chromosome architecture and cell functions of single cells.

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DeTOKI identifies and characterizes the dynamics of chromatin TAD-like domains in a single cell

Cited by 23 publications

References 69 publications

DeDoc2 identifies and characterizes the hierarchy and dynamics of chromatin TAD-like domains in the single cells

DeDoc2 identifies and characterizes the hierarchy and dynamics of chromatin TAD-like domains in the single cells

Mapping nucleosome and chromatin architectures: A survey of computational methods

Deciphering Hierarchical Chromatin Domains and Preference of Genomic Position Forming Boundaries in Single Mouse Embryonic Stem Cells

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