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SuperTAD: robust detection of hierarchical topologically associated domains with optimized structural information

Topologically associating domains (TADs) are the organizational units of chromosome structures. TADs can contain TADs, thus forming a hierarchy. TAD hierarchies can be inferred from Hi-C data through coding trees. However, the current method for computing coding trees is not optimal. In this paper,...

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Detalles Bibliográficos
Autores principales: Zhang, Yu Wei, Wang, Meng Bo, Li, Shuai Cheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7831269/
https://www.ncbi.nlm.nih.gov/pubmed/33494803
http://dx.doi.org/10.1186/s13059-020-02234-6
Descripción
Sumario:Topologically associating domains (TADs) are the organizational units of chromosome structures. TADs can contain TADs, thus forming a hierarchy. TAD hierarchies can be inferred from Hi-C data through coding trees. However, the current method for computing coding trees is not optimal. In this paper, we propose optimal algorithms for this computation. In comparison with seven state-of-art methods using two public datasets, from GM12878 and IMR90 cells, SuperTAD shows a significant enrichment of structural proteins around detected boundaries and histone modifications within TADs and displays a high consistency between various resolutions of identical Hi-C matrices. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1186/s13059-020-02234-6).