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.

Comparison of computational methods for Hi-C data analysis

Ferrari F;
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.
2017
Istituto di Genetica Molecolare "Luigi Luca Cavalli Sforza"
Inglese
14
7
679
685
http://www.scopus.com/inward/record.url?eid=2-s2.0-85027494899&partnerID=q2rCbXpz
Sì, ma tipo non specificato
Hi-C data
bioinformatics
6
info:eu-repo/semantics/article
262
Forcato, M; Nicoletti, C; Pal, K; Livi, Cm; Ferrari, F; Bicciato, S
01 Contributo su Rivista::01.01 Articolo in rivista
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/350925
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