The DOI matches its Crossref record; 41 of the 41 references it cites were found in a registry or an index.
Comparison of computational methods for Hi-C data analysis
Open accessAbstract
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.
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Cites
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Cited by
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Distinct Classes of Chromatin Loops Revealed by Deletion of an RNA-Binding Region in CTCF
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Identifying statistically significant chromatin contacts from Hi-C data with FitHiC2
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Metadata
- Authors
- Forcato, M., Nicoletti, C., Pal, K., Livi, C. M., Ferrari, F., & Bicciato, S.
- Venue
- Nature Methods
- Published
- 2017-06-12
- Volume
- 14
- Issue
- 7
- Pages
- 679-685
- ISSN
- 1548-7091 (ISSN-L)
- 1548-7105
- OpenAlex
- W2625231465
- Cited by
- 312
- References
- 41
- FWCI
- 14.85
- Type
- journal article
- Language
- en
- Open access
- green
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- Forcato, M., Nicoletti, C., Pal, K., Livi, C. M., Ferrari, F., & Bicciato, S. (2017). Comparison of computational methods for Hi-C data analysis. Nature Methods. https://doi.org/10.1038/nmeth.4325
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