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Nat Methods. 2017 Jul;14(7):679-685. doi: 10.1038/nmeth.4325. Epub 2017 Jun 12.

Comparison of computational methods for Hi-C data analysis.

Author information

1
Dept. of Life Sciences, Center for Genome Research, University of Modena and Reggio Emilia, Modena, Italy.
2
IFOM - The FIRC Institute of Molecular Oncology, Milan, Italy.
3
Institute of Molecular Genetics, National Research Council, Pavia, Italy.
#
Contributed equally

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.

PMID:
28604721
PMCID:
PMC5493985
DOI:
10.1038/nmeth.4325
[Indexed for MEDLINE]
Free PMC Article

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