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Software tools for visualizing Hi-C data

High-throughput assays for measuring the three-dimensional (3D) configuration of DNA have provided unprecedented insights into the relationship between DNA 3D configuration and function. Data interpretation from assays such as ChIA-PET and Hi-C is challenging because the data is large and cannot be...

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Detalles Bibliográficos
Autores principales: Yardımcı, Galip Gürkan, Noble, William Stafford
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5290626/
https://www.ncbi.nlm.nih.gov/pubmed/28159004
http://dx.doi.org/10.1186/s13059-017-1161-y
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author Yardımcı, Galip Gürkan
Noble, William Stafford
author_facet Yardımcı, Galip Gürkan
Noble, William Stafford
author_sort Yardımcı, Galip Gürkan
collection PubMed
description High-throughput assays for measuring the three-dimensional (3D) configuration of DNA have provided unprecedented insights into the relationship between DNA 3D configuration and function. Data interpretation from assays such as ChIA-PET and Hi-C is challenging because the data is large and cannot be easily rendered using standard genome browsers. An effective Hi-C visualization tool must provide several visualization modes and be capable of viewing the data in conjunction with existing, complementary data. We review five software tools that do not require programming expertise. We summarize their complementary functionalities, and highlight which tool is best equipped for specific tasks. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-017-1161-y) contains supplementary material, which is available to authorized users.
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spelling pubmed-52906262017-02-07 Software tools for visualizing Hi-C data Yardımcı, Galip Gürkan Noble, William Stafford Genome Biol Review High-throughput assays for measuring the three-dimensional (3D) configuration of DNA have provided unprecedented insights into the relationship between DNA 3D configuration and function. Data interpretation from assays such as ChIA-PET and Hi-C is challenging because the data is large and cannot be easily rendered using standard genome browsers. An effective Hi-C visualization tool must provide several visualization modes and be capable of viewing the data in conjunction with existing, complementary data. We review five software tools that do not require programming expertise. We summarize their complementary functionalities, and highlight which tool is best equipped for specific tasks. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-017-1161-y) contains supplementary material, which is available to authorized users. BioMed Central 2017-02-03 /pmc/articles/PMC5290626/ /pubmed/28159004 http://dx.doi.org/10.1186/s13059-017-1161-y Text en © The Author(s) 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Review
Yardımcı, Galip Gürkan
Noble, William Stafford
Software tools for visualizing Hi-C data
title Software tools for visualizing Hi-C data
title_full Software tools for visualizing Hi-C data
title_fullStr Software tools for visualizing Hi-C data
title_full_unstemmed Software tools for visualizing Hi-C data
title_short Software tools for visualizing Hi-C data
title_sort software tools for visualizing hi-c data
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5290626/
https://www.ncbi.nlm.nih.gov/pubmed/28159004
http://dx.doi.org/10.1186/s13059-017-1161-y
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