Comparison of computational methods for the identification of topologically associating domains
Abstract Background Chromatin folding gives rise to structural elements among which are clusters of densely interacting DNA regions termed topologically associating domains (TADs). TADs have been characterized across multiple species, tissue types, and differentiation stages, sometimes in associatio...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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BMC
2018-12-01
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| Series: | Genome Biology |
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| Online Access: | http://link.springer.com/article/10.1186/s13059-018-1596-9 |
| _version_ | 1819069247847923712 |
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| author | Marie Zufferey Daniele Tavernari Elisa Oricchio Giovanni Ciriello |
| author_facet | Marie Zufferey Daniele Tavernari Elisa Oricchio Giovanni Ciriello |
| author_sort | Marie Zufferey |
| collection | DOAJ |
| description | Abstract Background Chromatin folding gives rise to structural elements among which are clusters of densely interacting DNA regions termed topologically associating domains (TADs). TADs have been characterized across multiple species, tissue types, and differentiation stages, sometimes in association with regulation of biological functions. The reliability and reproducibility of these findings are intrinsically related with the correct identification of these domains from high-throughput chromatin conformation capture (Hi-C) experiments. Results Here, we test and compare 22 computational methods to identify TADs across 20 different conditions. We find that TAD sizes and numbers vary significantly among callers and data resolutions, challenging the definition of an average TAD size, but strengthening the hypothesis that TADs are hierarchically organized domains, rather than disjoint structural elements. Performances of these methods differ based on data resolution and normalization strategy, but a core set of TAD callers consistently retrieve reproducible domains, even at low sequencing depths, that are enriched for TAD-associated biological features. Conclusions This study provides a reference for the analysis of chromatin domains from Hi-C experiments and useful guidelines for choosing a suitable approach based on the experimental design, available data, and biological question of interest. |
| first_indexed | 2024-12-21T16:47:01Z |
| format | Article |
| id | doaj.art-7cd03966c5d74008a9f0a1fbe897f9b9 |
| institution | Directory Open Access Journal |
| issn | 1474-760X |
| language | English |
| last_indexed | 2024-12-21T16:47:01Z |
| publishDate | 2018-12-01 |
| publisher | BMC |
| record_format | Article |
| series | Genome Biology |
| spelling | doaj.art-7cd03966c5d74008a9f0a1fbe897f9b92022-12-21T18:56:58ZengBMCGenome Biology1474-760X2018-12-0119111810.1186/s13059-018-1596-9Comparison of computational methods for the identification of topologically associating domainsMarie Zufferey0Daniele Tavernari1Elisa Oricchio2Giovanni Ciriello3Department of Computational Biology, University of Lausanne (UNIL)Department of Computational Biology, University of Lausanne (UNIL)Swiss Institute for Experimental Cancer Research (ISREC), School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL)Department of Computational Biology, University of Lausanne (UNIL)Abstract Background Chromatin folding gives rise to structural elements among which are clusters of densely interacting DNA regions termed topologically associating domains (TADs). TADs have been characterized across multiple species, tissue types, and differentiation stages, sometimes in association with regulation of biological functions. The reliability and reproducibility of these findings are intrinsically related with the correct identification of these domains from high-throughput chromatin conformation capture (Hi-C) experiments. Results Here, we test and compare 22 computational methods to identify TADs across 20 different conditions. We find that TAD sizes and numbers vary significantly among callers and data resolutions, challenging the definition of an average TAD size, but strengthening the hypothesis that TADs are hierarchically organized domains, rather than disjoint structural elements. Performances of these methods differ based on data resolution and normalization strategy, but a core set of TAD callers consistently retrieve reproducible domains, even at low sequencing depths, that are enriched for TAD-associated biological features. Conclusions This study provides a reference for the analysis of chromatin domains from Hi-C experiments and useful guidelines for choosing a suitable approach based on the experimental design, available data, and biological question of interest.http://link.springer.com/article/10.1186/s13059-018-1596-9Topologically associating domainHi-CMethod comparison |
| spellingShingle | Marie Zufferey Daniele Tavernari Elisa Oricchio Giovanni Ciriello Comparison of computational methods for the identification of topologically associating domains Genome Biology Topologically associating domain Hi-C Method comparison |
| title | Comparison of computational methods for the identification of topologically associating domains |
| title_full | Comparison of computational methods for the identification of topologically associating domains |
| title_fullStr | Comparison of computational methods for the identification of topologically associating domains |
| title_full_unstemmed | Comparison of computational methods for the identification of topologically associating domains |
| title_short | Comparison of computational methods for the identification of topologically associating domains |
| title_sort | comparison of computational methods for the identification of topologically associating domains |
| topic | Topologically associating domain Hi-C Method comparison |
| url | http://link.springer.com/article/10.1186/s13059-018-1596-9 |
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