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Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/192213
4Cin: A computational pipeline for 3D genome modeling and virtual Hi-C analyses from 4C dataGómez-Skarmeta
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The use of 3C-based methods has revealed the importance of the 3D organization of the chromatin for key aspects of genome biology. However, the different caveats of the variants of 3C techniques have limited their scope and the range of scientific fields that could benefit from these approaches. To address these limitations, we present 4Cin, a method to gener-ate 3D models and derive virtual Hi-C (vHi-C) heat maps of genomic loci based on 4C-seq or any kind of 4C-seq-like data, such as those derived from NG Capture-C. 3D genome organization is determined by integrative consideration of the spatial distances derived from as few as four 4C-seq experiments. The 3D models obtained from 4C-seq data, together with their associated vHi-C maps, allow the inference of all chromosomal contacts within a given genomic region, facilitating the identification of Topological Associating Domains (TAD) boundaries. Thus, 4Cin offers a much cheaper, accessible and versatile alternative to other available techniques while providing a comprehensive 3D topological profiling. By studying TAD modifications in genomic structural variants associated to disease pheno-types and performing cross-species evolutionary comparisons of 3D chromatin structures in a quantitative manner, we demonstrate the broad potential and novel range of applications of our method.
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IRASTORZA-AZCARATE, Ibai, et al. 4Cin: A computational pipeline for 3D genome modeling and virtual Hi-C analyses from 4C dataGómez-Skarmeta. PLoS Computational Biology. 2018. Vol. 14, num. 3. ISSN 1553-734X. [consulted: 11 of October of 2026]. Available at: https://hdl.handle.net/2445/192213