FIREcaller: Detecting frequently interacting regions from Hi-C data

Cheynna Crowley; Yuchen Yang; Yunjiang Qiu; Benxia Hu; Armen Abnousi; Jakub Lipiński; Dariusz Plewczyński; Di Wu; Hyejung Won; Bing Ren; Ming Hu; Yun Li

doi:10.1016/j.csbj.2020.12.026

FIREcaller: Detecting frequently interacting regions from Hi-C data

Comput Struct Biotechnol J. 2020 Dec 29:19:355-362. doi: 10.1016/j.csbj.2020.12.026. eCollection 2021.

Authors

Cheynna Crowley^{1

2}, Yuchen Yang¹, Yunjiang Qiu^{3

4}, Benxia Hu^{1

5}, Armen Abnousi⁶, Jakub Lipiński⁷, Dariusz Plewczyński^{7

8}, Di Wu^{2

9}, Hyejung Won^{1

5}, Bing Ren^{3

10

11}, Ming Hu⁶, Yun Li^{1

2

12}

Affiliations

¹ Department of Genetics, University of North Carolina Chapel Hill, Chapel Hill, NC, USA.
² Department of Biostatistics, University of North Carolina Chapel Hill, Chapel Hill, NC, USA.
³ Ludwig Institute for Cancer Research, La Jolla, CA, USA.
⁴ Bioinformatics and Systems Biology Graduate Program, University of California San Diego, La Jolla, CA, USA.
⁵ UNC Neuroscience Center, University of North Carolina Chapel Hill, Chapel Hill, NC, USA.
⁶ Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA.
⁷ Cellular Genomics, Warsaw, Poland.
⁸ Department of Mathematics and Information Science, Warsaw University of Technology, Warszawa, Poland.
⁹ Division of Oral and Craniofacial Health Sciences, Adams School of Dentistry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
¹⁰ Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA.
¹¹ Institute of Genomic Medicine and Moores Cancer Center, University of California San Diego, La Jolla, CA, USA.
¹² Department of Computer Science, University of North Carolina Chapel Hill, Chapel Hill, NC, USA.

Abstract

Hi-C experiments have been widely adopted to study chromatin spatial organization, which plays an essential role in genome function. We have recently identified frequently interacting regions (FIREs) and found that they are closely associated with cell-type-specific gene regulation. However, computational tools for detecting FIREs from Hi-C data are still lacking. In this work, we present FIREcaller, a stand-alone, user-friendly R package for detecting FIREs from Hi-C data. FIREcaller takes raw Hi-C contact matrices as input, performs within-sample and cross-sample normalization, and outputs continuous FIRE scores, dichotomous FIREs, and super-FIREs. Applying FIREcaller to Hi-C data from various human tissues, we demonstrate that FIREs and super-FIREs identified, in a tissue-specific manner, are closely related to gene regulation, are enriched for enhancer-promoter (E-P) interactions, tend to overlap with regions exhibiting epigenomic signatures of cis-regulatory roles, and aid the interpretation or GWAS variants. The FIREcaller package is implemented in R and freely available at https://yunliweb.its.unc.edu/FIREcaller.

Keywords: Chromatin spatial organization; Frequently Interacting Regions (FIREs); Hi-C.

Abstract

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