FIREcaller: Detecting Frequently Interacting Regions from Hi-C Data

Overview

Journal Comput Struct Biotechnol J

Specialty Biotechnology

Date 2021 Jan 25

PMID 33489005

Citations 17

Authors

Cheynna Crowley

Yuchen Yang

Yunjiang Qiu

Benxia Hu

Armen Abnousi

Jakub Lipinski

Dariusz Plewczynski

Di Wu

Hyejung Won

Bing Ren

Ming Hu

Yun Li

Affiliations

Soon will be listed here.

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 -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.

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