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FIREcaller: Detecting frequently interacting regions from Hi-C data.
Crowley, Cheynna; Yang, Yuchen; Qiu, Yunjiang; Hu, Benxia; Abnousi, Armen; Lipinski, Jakub; Plewczynski, Dariusz; Wu, Di; Won, Hyejung; Ren, Bing; Hu, Ming; Li, Yun.
Afiliação
  • Crowley C; Department of Genetics, University of North Carolina Chapel Hill, Chapel Hill, NC, USA.
  • Yang Y; Department of Biostatistics, University of North Carolina Chapel Hill, Chapel Hill, NC, USA.
  • Qiu Y; Department of Genetics, University of North Carolina Chapel Hill, Chapel Hill, NC, USA.
  • Hu B; Ludwig Institute for Cancer Research, La Jolla, CA, USA.
  • Abnousi A; Bioinformatics and Systems Biology Graduate Program, University of California San Diego, La Jolla, CA, USA.
  • Lipinski J; Department of Genetics, University of North Carolina Chapel Hill, Chapel Hill, NC, USA.
  • Plewczynski D; UNC Neuroscience Center, University of North Carolina Chapel Hill, Chapel Hill, NC, USA.
  • Wu D; Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA.
  • Won H; Cellular Genomics, Warsaw, Poland.
  • Ren B; Cellular Genomics, Warsaw, Poland.
  • Hu M; Department of Mathematics and Information Science, Warsaw University of Technology, Warszawa, Poland.
  • Li Y; Department of Biostatistics, University of North Carolina Chapel Hill, Chapel Hill, NC, USA.
Comput Struct Biotechnol J ; 19: 355-362, 2021.
Article em En | MEDLINE | ID: mdl-33489005
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Comput Struct Biotechnol J Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Comput Struct Biotechnol J Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos