Decoding topologically associating domains with ultra-low resolution Hi-C data by graph structural entropy
Accurate detection of TADs requires ultra-deep sequencing and sophisticated normalisation procedures, which limits the analysis of Hi-C data. Here the authors develop a normalisation-free method to decode the domains of chromosomes (deDoc) that utilizes structural entropy to predict TADs with ultra-...
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| Autores principales: | , , , , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2018
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/46fdb2762a7445d7993295e078768865 |
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| Sumario: | Accurate detection of TADs requires ultra-deep sequencing and sophisticated normalisation procedures, which limits the analysis of Hi-C data. Here the authors develop a normalisation-free method to decode the domains of chromosomes (deDoc) that utilizes structural entropy to predict TADs with ultra-low sequencing data. |
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