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.
Original language | English (US) |
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Article number | 69 |
Journal | Genome Medicine |
Volume | 12 |
Issue number | 1 |
DOIs | |
State | Published - Aug 12 2020 |
ASJC Scopus subject areas
- Molecular Medicine
- Molecular Biology
- Genetics
- Genetics(clinical)