Modeling and analysis of Hi-C data by HiSIF identifies characteristic promoter-distal loops

Genome Med. 2020 Aug 12;12(1):69. doi: 10.1186/s13073-020-00769-8.

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 .

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Algorithms
  • Chromatin / genetics*
  • Computational Biology / methods*
  • Cytogenetics / methods*
  • Databases, Genetic
  • Genomics / methods*
  • Humans
  • Promoter Regions, Genetic*
  • ROC Curve
  • Reproducibility of Results
  • Software*

Substances

  • Chromatin