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FIREcaller: Detecting Frequently Interacting Regions from Hi-C Data

Cheynna Crowley, Yuchen Yang, Yunjiang Qiu, Benxia Hu, Armen Abnousi, Jakub Lipiński, Dariusz Plewczyński, View ORCID ProfileDi Wu, View ORCID ProfileHyejung Won, Bing Ren, Ming Hu, View ORCID ProfileYun Li
doi: https://doi.org/10.1101/619288
Cheynna Crowley
1Department of Genetics, University of North Carolina Chapel Hill, Chapel Hill, NC, USA.
2Department of Biostatistics, University of North Carolina Chapel Hill, Chapel Hill, NC, USA.
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Yuchen Yang
1Department of Genetics, University of North Carolina Chapel Hill, Chapel Hill, NC, USA.
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Yunjiang Qiu
3Ludwig Institute for Cancer Research, La Jolla, California, USA.
4Bioinformatics and Systems Biology Graduate Program, University of California San Diego, La Jolla, California, USA.
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Benxia Hu
1Department of Genetics, University of North Carolina Chapel Hill, Chapel Hill, NC, USA.
5UNC Neuroscience Center, University of North Carolina Chapel Hill, Chapel Hill, NC, USA.
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Armen Abnousi
6Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, Ohio, USA.
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Jakub Lipiński
7Cellular Genomics, Warsaw, Poland.
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Dariusz Plewczyński
7Cellular Genomics, Warsaw, Poland.
8Department of Mathematics and Information Science, Warsaw University of Technology, Warszawa, Poland.
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Di Wu
2Department of Biostatistics, University of North Carolina Chapel Hill, Chapel Hill, NC, USA.
9Division of Oral and Craniofacial Health Sciences, Adams School of Dentistry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
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  • ORCID record for Di Wu
Hyejung Won
1Department of Genetics, University of North Carolina Chapel Hill, Chapel Hill, NC, USA.
5UNC Neuroscience Center, University of North Carolina Chapel Hill, Chapel Hill, NC, USA.
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Bing Ren
3Ludwig Institute for Cancer Research, La Jolla, California, USA.
10Department of Cellular and Molecular Medicine, University of California San Diego. La Jolla, California USA.
11Institute of Genomic Medicine and Moores Cancer Center, University of California San Diego. La Jolla, California, USA.
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Ming Hu
6Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, Ohio, USA.
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  • For correspondence: hum@ccf.org
Yun Li
1Department of Genetics, University of North Carolina Chapel Hill, Chapel Hill, NC, USA.
2Department of Biostatistics, University of North Carolina Chapel Hill, Chapel Hill, NC, USA.
12Department of Computer Science, University of North Carolina Chapel Hill, Chapel Hill, NC, USA.
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  • For correspondence: hum@ccf.org
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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.

Highlights

  • – Frequently Interacting Regions (FIREs) can be used to identify tissue and cell-type-specific cis-regulatory regions.

  • – An R software, FIREcaller, has been developed to identify FIREs and clustered FIREs into super-FIREs.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • https://yunliweb.its.unc.edu/FIREcaller.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted December 20, 2020.
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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
bioRxiv 619288; doi: https://doi.org/10.1101/619288
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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
bioRxiv 619288; doi: https://doi.org/10.1101/619288

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