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HiCeekR: A Novel Shiny App for Hi-C Data Analysis.
Di Filippo, Lucio; Righelli, Dario; Gagliardi, Miriam; Matarazzo, Maria Rosaria; Angelini, Claudia.
Afiliação
  • Di Filippo L; Telethon Institute of Genetics and Medicine (TIGEM), Pozzuoli, Italy.
  • Righelli D; Istituto per le Applicazioni del Calcolo "Mauro Picone," Consiglio Nazionale delle Ricerche, Napoli, Italy.
  • Gagliardi M; Max Planck Institute for Psychiatry, Munich, Germany.
  • Matarazzo MR; Institute of Genetics and Biophysics "A. Buzzati A. Traverso," Consiglio Nazionale delle Ricerche, Napoli, Italy.
  • Angelini C; Institute of Genetics and Biophysics "A. Buzzati A. Traverso," Consiglio Nazionale delle Ricerche, Napoli, Italy.
Front Genet ; 10: 1079, 2019.
Article em En | MEDLINE | ID: mdl-31749839
ABSTRACT
The High-throughput Chromosome Conformation Capture (Hi-C) technique combines the power of the Next Generation Sequencing technologies with chromosome conformation capture approach to study the 3D chromatin organization at the genome-wide scale. Although such a technique is quite recent, many tools are already available for pre-processing and analyzing Hi-C data, allowing to identify chromatin loops, topological associating domains and A/B compartments. However, only a few of them provide an exhaustive analysis pipeline or allow to easily integrate and visualize other omic layers. Moreover, most of the available tools are designed for expert users, who have great confidence with command-line applications. In this paper, we present HiCeekR (https//github.com/lucidif/HiCeekR), a novel R Graphical User Interface (GUI) that allows researchers to easily perform a complete Hi-C data analysis. With the aid of the Shiny libraries, it integrates several R/Bioconductor packages for Hi-C data analysis and visualization, guiding the user during the entire process. Here, we describe its architecture and functionalities, then illustrate its capabilities using a publicly available dataset.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2019 Tipo de documento: Article