Comparison of computational methods for the identification of topologically associating domains.
- Zufferey M Department of Computational Biology, University of Lausanne (UNIL), Lausanne, Switzerland.
- Tavernari D Department of Computational Biology, University of Lausanne (UNIL), Lausanne, Switzerland.
- Oricchio E Swiss Institute for Experimental Cancer Research (ISREC), School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
- Ciriello G Department of Computational Biology, University of Lausanne (UNIL), Lausanne, Switzerland. giovanni.ciriello@unil.ch.
- 2018-12-12
Published in:
- Genome biology. - 2018
Hi-C
Method comparison
Topologically associating domain
Animals
Chromatin Assembly and Disassembly
Chromosomes
Genomics
Humans
Mice
English
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.
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.
- Language
-
- English
- Open access status
- gold
- Identifiers
-
- DOI 10.1186/s13059-018-1596-9
- PMID 30526631
- Persistent URL
- https://sonar.ch/global/documents/24326
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