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Comparison of computational methods for Hi-C data analysis.

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.

SUBMITTER: Forcato M

PROVIDER: S-EPMC5493985 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

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Comparison of computational methods for Hi-C data analysis.

Forcato Mattia M Nicoletti Chiara C Pal Koustav K Livi Carmen Maria CM Ferrari Francesco F Bicciato Silvio S

Nature methods 20170612 7

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 chroma ...[more]

PMID: 28604721

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