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HiCEnterprise: identifying long range chromosomal contacts in Hi-C data

MOTIVATION: Computational analysis of chromosomal contact data is currently gaining popularity with the rapid advance in experimental techniques providing access to a growing body of data. An important problem in this area is the identification of long range contacts between distinct chromatin regio...

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Detalles Bibliográficos
Autores principales: Kranas, Hanna, Tuszynska, Irina, Wilczynski, Bartek
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8083178/
https://www.ncbi.nlm.nih.gov/pubmed/33981483
http://dx.doi.org/10.7717/peerj.10558
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author Kranas, Hanna
Tuszynska, Irina
Wilczynski, Bartek
author_facet Kranas, Hanna
Tuszynska, Irina
Wilczynski, Bartek
author_sort Kranas, Hanna
collection PubMed
description MOTIVATION: Computational analysis of chromosomal contact data is currently gaining popularity with the rapid advance in experimental techniques providing access to a growing body of data. An important problem in this area is the identification of long range contacts between distinct chromatin regions. Such loops were shown to exist at different scales, either mediating relatively short range interactions between enhancers and promoters or providing interactions between much larger, distant chromosome domains. A proper statistical analysis as well as availability to a wide research community are crucial in a tool for this task. RESULTS: We present HiCEnterprise, a first freely available software tool for identification of long range chromatin contacts not only between small regions, but also between chromosomal domains. It implements four different statistical tests for identification of significant contacts for user defined regions or domains as well as necessary functions for input, output and visualization of chromosome contacts. AVAILABILITY: The software and the corresponding documentation are available at: github.com/regulomics/HiCEnterprise. SUPPLEMENTARY INFORMATION: Supplemental data are available in the online version of the article and at the website regulomics.mimuw.edu.pl/wp/hicenterprise.
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spelling pubmed-80831782021-05-11 HiCEnterprise: identifying long range chromosomal contacts in Hi-C data Kranas, Hanna Tuszynska, Irina Wilczynski, Bartek PeerJ Bioinformatics MOTIVATION: Computational analysis of chromosomal contact data is currently gaining popularity with the rapid advance in experimental techniques providing access to a growing body of data. An important problem in this area is the identification of long range contacts between distinct chromatin regions. Such loops were shown to exist at different scales, either mediating relatively short range interactions between enhancers and promoters or providing interactions between much larger, distant chromosome domains. A proper statistical analysis as well as availability to a wide research community are crucial in a tool for this task. RESULTS: We present HiCEnterprise, a first freely available software tool for identification of long range chromatin contacts not only between small regions, but also between chromosomal domains. It implements four different statistical tests for identification of significant contacts for user defined regions or domains as well as necessary functions for input, output and visualization of chromosome contacts. AVAILABILITY: The software and the corresponding documentation are available at: github.com/regulomics/HiCEnterprise. SUPPLEMENTARY INFORMATION: Supplemental data are available in the online version of the article and at the website regulomics.mimuw.edu.pl/wp/hicenterprise. PeerJ Inc. 2021-04-26 /pmc/articles/PMC8083178/ /pubmed/33981483 http://dx.doi.org/10.7717/peerj.10558 Text en © 2021 Kranas et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Bioinformatics
Kranas, Hanna
Tuszynska, Irina
Wilczynski, Bartek
HiCEnterprise: identifying long range chromosomal contacts in Hi-C data
title HiCEnterprise: identifying long range chromosomal contacts in Hi-C data
title_full HiCEnterprise: identifying long range chromosomal contacts in Hi-C data
title_fullStr HiCEnterprise: identifying long range chromosomal contacts in Hi-C data
title_full_unstemmed HiCEnterprise: identifying long range chromosomal contacts in Hi-C data
title_short HiCEnterprise: identifying long range chromosomal contacts in Hi-C data
title_sort hicenterprise: identifying long range chromosomal contacts in hi-c data
topic Bioinformatics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8083178/
https://www.ncbi.nlm.nih.gov/pubmed/33981483
http://dx.doi.org/10.7717/peerj.10558
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