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HiCeekR: A Novel Shiny App for Hi-C Data Analysis
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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6844183/ https://www.ncbi.nlm.nih.gov/pubmed/31749839 http://dx.doi.org/10.3389/fgene.2019.01079 |
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author | Di Filippo, Lucio Righelli, Dario Gagliardi, Miriam Matarazzo, Maria Rosaria Angelini, Claudia |
author_facet | Di Filippo, Lucio Righelli, Dario Gagliardi, Miriam Matarazzo, Maria Rosaria Angelini, Claudia |
author_sort | Di Filippo, Lucio |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6844183 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-68441832019-11-20 HiCeekR: A Novel Shiny App for Hi-C Data Analysis Di Filippo, Lucio Righelli, Dario Gagliardi, Miriam Matarazzo, Maria Rosaria Angelini, Claudia Front Genet Genetics 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. Frontiers Media S.A. 2019-11-04 /pmc/articles/PMC6844183/ /pubmed/31749839 http://dx.doi.org/10.3389/fgene.2019.01079 Text en Copyright © 2019 Di Filippo, Righelli, Gagliardi, Matarazzo and Angelini http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Di Filippo, Lucio Righelli, Dario Gagliardi, Miriam Matarazzo, Maria Rosaria Angelini, Claudia HiCeekR: A Novel Shiny App for Hi-C Data Analysis |
title | HiCeekR: A Novel Shiny App for Hi-C Data Analysis |
title_full | HiCeekR: A Novel Shiny App for Hi-C Data Analysis |
title_fullStr | HiCeekR: A Novel Shiny App for Hi-C Data Analysis |
title_full_unstemmed | HiCeekR: A Novel Shiny App for Hi-C Data Analysis |
title_short | HiCeekR: A Novel Shiny App for Hi-C Data Analysis |
title_sort | hiceekr: a novel shiny app for hi-c data analysis |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6844183/ https://www.ncbi.nlm.nih.gov/pubmed/31749839 http://dx.doi.org/10.3389/fgene.2019.01079 |
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