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HiCBricks: building blocks for efficient handling of large Hi-C datasets

SUMMARY: Genome-wide chromosome conformation capture based on high-throughput sequencing (Hi-C) has been widely adopted to study chromatin architecture by generating datasets of ever-increasing complexity and size. HiCBricks offers user-friendly and efficient solutions for handling large high-resolu...

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Detalles Bibliográficos
Autores principales: Pal, Koustav, Tagliaferri, Ilario, Livi, Carmen Maria, Ferrari, Francesco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7703765/
https://www.ncbi.nlm.nih.gov/pubmed/31697323
http://dx.doi.org/10.1093/bioinformatics/btz808
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author Pal, Koustav
Tagliaferri, Ilario
Livi, Carmen Maria
Ferrari, Francesco
author_facet Pal, Koustav
Tagliaferri, Ilario
Livi, Carmen Maria
Ferrari, Francesco
author_sort Pal, Koustav
collection PubMed
description SUMMARY: Genome-wide chromosome conformation capture based on high-throughput sequencing (Hi-C) has been widely adopted to study chromatin architecture by generating datasets of ever-increasing complexity and size. HiCBricks offers user-friendly and efficient solutions for handling large high-resolution Hi-C datasets. The package provides an R/Bioconductor framework with the bricks to build more complex data analysis pipelines and algorithms. HiCBricks already incorporates functions for calling domain boundaries and functions for high-quality data visualization. AVAILABILITY AND IMPLEMENTATION: http://bioconductor.org/packages/devel/bioc/html/HiCBricks.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-77037652020-12-07 HiCBricks: building blocks for efficient handling of large Hi-C datasets Pal, Koustav Tagliaferri, Ilario Livi, Carmen Maria Ferrari, Francesco Bioinformatics Applications Note SUMMARY: Genome-wide chromosome conformation capture based on high-throughput sequencing (Hi-C) has been widely adopted to study chromatin architecture by generating datasets of ever-increasing complexity and size. HiCBricks offers user-friendly and efficient solutions for handling large high-resolution Hi-C datasets. The package provides an R/Bioconductor framework with the bricks to build more complex data analysis pipelines and algorithms. HiCBricks already incorporates functions for calling domain boundaries and functions for high-quality data visualization. AVAILABILITY AND IMPLEMENTATION: http://bioconductor.org/packages/devel/bioc/html/HiCBricks.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2020-03-15 2019-11-07 /pmc/articles/PMC7703765/ /pubmed/31697323 http://dx.doi.org/10.1093/bioinformatics/btz808 Text en © The Author(s) 2019. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Note
Pal, Koustav
Tagliaferri, Ilario
Livi, Carmen Maria
Ferrari, Francesco
HiCBricks: building blocks for efficient handling of large Hi-C datasets
title HiCBricks: building blocks for efficient handling of large Hi-C datasets
title_full HiCBricks: building blocks for efficient handling of large Hi-C datasets
title_fullStr HiCBricks: building blocks for efficient handling of large Hi-C datasets
title_full_unstemmed HiCBricks: building blocks for efficient handling of large Hi-C datasets
title_short HiCBricks: building blocks for efficient handling of large Hi-C datasets
title_sort hicbricks: building blocks for efficient handling of large hi-c datasets
topic Applications Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7703765/
https://www.ncbi.nlm.nih.gov/pubmed/31697323
http://dx.doi.org/10.1093/bioinformatics/btz808
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