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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2512.17512 |
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| _version_ | 1866909970935578624 |
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| author | Kumar, Vipin Rossini, Roberto Paulsen, Jonas Mathelier, Anthony |
| author_facet | Kumar, Vipin Rossini, Roberto Paulsen, Jonas Mathelier, Anthony |
| contents | Chromatin conformation capture technologies such as Hi-C have revealed that the genome is organized in a hierarchy of structures spanning multiple scales observed at different resolutions. Current algorithms often focus on specific interaction patterns found at a specific Hi-C resolution. We present BHi-Cect 2.0, a method that leverages Hi-C data at multiple resolutions to describe chromosome architecture as nested preferentially self-interacting clusters using spectral clustering. This new version describes the hierarchical configuration of chromosomes by now integrating multiple Hi-C data resolutions. Our new implementation offers a more comprehensive description of the multi-scale architecture of the chromosomes. We further provide these functionalities as an R package to assist their integration with other computational pipelines. The BHiCect 2.0 R packages is available on github at https://github.com/princeps091-binf/BHiCect2with the version used for this manuscript on Zenodo at https://doi.org/10.5281/zenodo.17985844. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_17512 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | BHiCect 2.0: Multi-resolution clustering of Hi-C data Kumar, Vipin Rossini, Roberto Paulsen, Jonas Mathelier, Anthony Genomics Chromatin conformation capture technologies such as Hi-C have revealed that the genome is organized in a hierarchy of structures spanning multiple scales observed at different resolutions. Current algorithms often focus on specific interaction patterns found at a specific Hi-C resolution. We present BHi-Cect 2.0, a method that leverages Hi-C data at multiple resolutions to describe chromosome architecture as nested preferentially self-interacting clusters using spectral clustering. This new version describes the hierarchical configuration of chromosomes by now integrating multiple Hi-C data resolutions. Our new implementation offers a more comprehensive description of the multi-scale architecture of the chromosomes. We further provide these functionalities as an R package to assist their integration with other computational pipelines. The BHiCect 2.0 R packages is available on github at https://github.com/princeps091-binf/BHiCect2with the version used for this manuscript on Zenodo at https://doi.org/10.5281/zenodo.17985844. |
| title | BHiCect 2.0: Multi-resolution clustering of Hi-C data |
| topic | Genomics |
| url | https://arxiv.org/abs/2512.17512 |