A comprehensive review and benchmark of differential analysis tools for Hi-C data
Résumé
Motivation The 3D organization of the genome plays a crucial role in various biological processes. Hi-C technology is widely used to investigate chromosome structures by quantifying 3D proximity between genomic regions. While numerous computational tools exist for detecting differences in Hi-C data between conditions, a comprehensive review and benchmark comparing their effectiveness is lacking. Results This study offers a comprehensive review and benchmark of 10 generic tools for differential analysis of Hi-C matrices at the interaction count level. The benchmark assesses the statistical methods, usability, and performance (in terms of precision and power) of these tools, using both real and simulated Hi-C data. Results reveal a striking variability in performance among the tools, highlighting the substantial impact of preprocessing filters and the difficulty all tools encounter in effectively controlling the false discovery rate across varying resolutions and chromosome sizes. Availability The complete benchmark is available at https://forgemia.inra.fr/scales/replication-chrocodiff using processed data deposited at https://doi.org/10.57745/LR0W9R. Contact nathalie.vialaneix@inrae.fr
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Est complété par 10.57745/LR0W9R Jeu de données Vialaneix, N., & Foissac, S. (2024). Replication dataset for ‘A comprehensive review and benchmark of differential analysis tools for Hi-C data’ [Data set]. Recherche Data Gouv. https://doi.org/10.57745/LR0W9R
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Cite 10.57745/LR0W9R Jeu de données Vialaneix, N., & Foissac, S. (2024). Replication dataset for ‘A comprehensive review and benchmark of differential analysis tools for Hi-C data’ [Data set]. Recherche Data Gouv. https://doi.org/10.57745/LR0W9R