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FIREcaller: Detecting frequently interacting regions from Hi-C data.

Cheynna Crowley1,2, Yuchen Yang1, Yunjiang Qiu3,4

  • 1Department of Genetics, University of North Carolina Chapel Hill, Chapel Hill, NC, USA.

Computational and Structural Biotechnology Journal
|January 25, 2021
PubMed
Summary

We developed FIREcaller, an R package to identify frequently interacting regions (FIREs) from Hi-C data. FIREcaller aids in understanding tissue-specific gene regulation and interpreting genetic variants.

Keywords:
Chromatin spatial organizationFrequently Interacting Regions (FIREs)Hi-C

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Area of Science:

  • Genomics
  • Molecular Biology
  • Bioinformatics

Background:

  • Chromatin spatial organization is crucial for genome function and gene regulation.
  • Frequently Interacting Regions (FIREs) are linked to cell-type-specific gene regulation.
  • Lack of computational tools hinders FIRE detection from Hi-C data.

Purpose of the Study:

  • Introduce FIREcaller, a user-friendly R package for detecting FIREs from Hi-C data.
  • Provide a computational solution for analyzing chromatin organization and its regulatory roles.

Main Methods:

  • FIREcaller processes raw Hi-C contact matrices.
  • It performs within-sample and cross-sample normalization.
  • Outputs include continuous FIRE scores, dichotomous FIREs, and super-FIREs.

Main Results:

  • FIREcaller successfully identified tissue-specific FIREs and super-FIREs across human tissues.
  • Identified FIREs correlate with gene regulation and enhancer-promoter interactions.
  • FIREs overlap with epigenomic signatures of cis-regulatory elements and aid GWAS variant interpretation.

Conclusions:

  • FIREcaller is an effective tool for detecting FIREs from Hi-C data.
  • FIREs and super-FIREs are significant in tissue-specific gene regulation and genomic interpretation.
  • The R package is freely available for research use.