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Comparison of computational methods for Hi-C data analysis

Articolo
Data di Pubblicazione:
2017
Abstract:
Hi-C is a genome-wide sequencing technique used to investigate 3D chromatin conformation inside the nucleus. Computational methods are required to analyze Hi-C data and identify chromatin interactions and topologically associating domains (TADs) from genome-wide contact probability maps. We quantitatively compared the performance of 13 algorithms in their analyses of Hi-C data from six landmark studies and simulations. This comparison revealed differences in the performance of methods for chromatin interaction identification, but more comparable results for TAD detection between algorithms.
Tipologia CRIS:
01.01 Articolo in rivista
Keywords:
Hi-C data; bioinformatics
Elenco autori:
Ferrari, Francesco
Autori di Ateneo:
FERRARI FRANCESCO
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/350925
Pubblicato in:
NATURE METHODS (ONLINE)
Journal
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http://www.scopus.com/inward/record.url?eid=2-s2.0-85027494899&partnerID=q2rCbXpz
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