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chromswitch: a flexible method to detect chromatin state switches

SUMMARY: Chromatin state plays a major role in controlling gene expression, and comparative analysis of ChIP-seq data is key to understanding epigenetic regulation. We present chromswitch, an R/Bioconductor package to integrate epigenomic data in a defined window of interest to detect an overall swi...

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Detalles Bibliográficos
Autores principales: Jessa, Selin, Kleinman, Claudia L
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6022667/
https://www.ncbi.nlm.nih.gov/pubmed/29438498
http://dx.doi.org/10.1093/bioinformatics/bty075
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author Jessa, Selin
Kleinman, Claudia L
author_facet Jessa, Selin
Kleinman, Claudia L
author_sort Jessa, Selin
collection PubMed
description SUMMARY: Chromatin state plays a major role in controlling gene expression, and comparative analysis of ChIP-seq data is key to understanding epigenetic regulation. We present chromswitch, an R/Bioconductor package to integrate epigenomic data in a defined window of interest to detect an overall switch in chromatin state. Chromswitch accurately classifies a benchmarking dataset, and when applied genome-wide, the tool successfully detects chromatin changes that result in brain-specific expression. AVAILABILITY AND IMPLEMENTATION: Chromswitch is implemented as an R package available from Bioconductor at https://bioconductor.org/packages/chromswitch. All data and code for reproducing the analysis presented in this paper are available at https://doi.org/10.5281/zenodo.1101260. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-60226672018-07-10 chromswitch: a flexible method to detect chromatin state switches Jessa, Selin Kleinman, Claudia L Bioinformatics Applications Notes SUMMARY: Chromatin state plays a major role in controlling gene expression, and comparative analysis of ChIP-seq data is key to understanding epigenetic regulation. We present chromswitch, an R/Bioconductor package to integrate epigenomic data in a defined window of interest to detect an overall switch in chromatin state. Chromswitch accurately classifies a benchmarking dataset, and when applied genome-wide, the tool successfully detects chromatin changes that result in brain-specific expression. AVAILABILITY AND IMPLEMENTATION: Chromswitch is implemented as an R package available from Bioconductor at https://bioconductor.org/packages/chromswitch. All data and code for reproducing the analysis presented in this paper are available at https://doi.org/10.5281/zenodo.1101260. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2018-07-01 2018-02-09 /pmc/articles/PMC6022667/ /pubmed/29438498 http://dx.doi.org/10.1093/bioinformatics/bty075 Text en © The Author(s) 2018. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Applications Notes
Jessa, Selin
Kleinman, Claudia L
chromswitch: a flexible method to detect chromatin state switches
title chromswitch: a flexible method to detect chromatin state switches
title_full chromswitch: a flexible method to detect chromatin state switches
title_fullStr chromswitch: a flexible method to detect chromatin state switches
title_full_unstemmed chromswitch: a flexible method to detect chromatin state switches
title_short chromswitch: a flexible method to detect chromatin state switches
title_sort chromswitch: a flexible method to detect chromatin state switches
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6022667/
https://www.ncbi.nlm.nih.gov/pubmed/29438498
http://dx.doi.org/10.1093/bioinformatics/bty075
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