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- Title
Modeling and analysis of Hi-C data by HiSIF identifies characteristic promoter-distal loops.
- Authors
Zhou, Yufan; Cheng, Xiaolong; Yang, Yini; Li, Tian; Li, Jingwei; Huang, Tim H.-M.; Wang, Junbai; Lin, Shili; Jin, Victor X.
- Abstract
Current computational methods on Hi-C analysis focused on identifying Mb-size domains often failed to unveil the underlying functional and mechanistic relationship of chromatin structure and gene regulation. We developed a novel computational method HiSIF to identify genome-wide interacting loci. We illustrated HiSIF outperformed other tools for identifying chromatin loops. We applied it to Hi-C data in breast cancer cells and identified 21 genes with gained loops showing worse relapse-free survival in endocrine-treated patients, suggesting the genes with enhanced loops can be used for prognostic signatures for measuring the outcome of the endocrine treatment. HiSIF is available at https://github.com/yufanzhouonline/HiSIF.
- Subjects
DATA analysis; GENETIC regulation; TREATMENT effectiveness; CANCER cells; BREAST cancer
- Publication
Genome Medicine, 2020, Vol 12, Issue 1, p1
- ISSN
1756-994X
- Publication type
Article
- DOI
10.1186/s13073-020-00769-8