HiConfidence: a novel approach uncovering the biological signal in Hi-C data affected by technical biases

Kobets, V.A.; Ulianov, S.V.; Galitsyna, A.A.; Doronin, S.A.; Mikhaleva, E.A.; Gelfand, M.S.; Shevelyov, Y.Y.; Razin, S.V.; Khrameeva, E.E.

Авторы: Kobets Victoria A., Ulianov Sergey V., Galitsyna Aleksandra A., Doronin Semen A., Mikhaleva Elena A., Gelfand Mikhail S., Shevelyov Yuri Y., Razin Sergey V., Khrameeva Ekaterina E.
Журнал: Briefings in Bioinformatics
Год издания: 2023
Издательство: Oxford University Press
Местоположение издательства: United Kingdom
DOI: 10.1093/bib/bbad044
Аннотация: The chromatin interaction assays, particularly Hi-C, enable detailed studies of genome architecture in multiple organisms and model systems, resulting in a deeper understanding of gene expression regulation mechanisms mediated by epigenetics. However, the analysis and interpretation of Hi-C data remain challenging due to technical biases, limiting direct comparisons of datasets obtained in different experiments and laboratories. As a result, removing biases from Hi-C-generated chromatin contact matrices is a critical data analysis step. Our novel approach, HiConfidence, eliminates biases from the Hi-C data by weighing chromatin contacts according to their consistency between replicates so that low-quality replicates do not substantially influence the result. The algorithm is effective for the analysis of global changes in chromatin structures such as compartments and topologically associating domains. We apply the HiConfidence approach to several Hi-C datasets with significant technical biases, that could not be analyzed effectively using existing methods, and obtain meaningful biological conclusions. In particular, HiConfidence aids in the study of how changes in histone acetylation pattern affect chromatin organization in Drosophila melanogaster S2 cells. The method is freely available at GitHub: https://github.com/victorykobets/HiConfidence.
Добавил в систему: Ульянов Сергей Владимирович

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HiConfidence: a novel approach uncovering the biological signal in Hi-C data affected by technical biasesстатья Исследовательская статья

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