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Identification of active regulatory regions from DNA methylation data
We have recently shown that transcription factor binding leads to defined reduction in DNA methylation, allowing for the identification of active regulatory regions from high-resolution methylomes. Here, we present MethylSeekR, a computational tool to accurately identify such footprints from bisulfi...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3763559/ https://www.ncbi.nlm.nih.gov/pubmed/23828043 http://dx.doi.org/10.1093/nar/gkt599 |
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author | Burger, Lukas Gaidatzis, Dimos Schübeler, Dirk Stadler, Michael B. |
author_facet | Burger, Lukas Gaidatzis, Dimos Schübeler, Dirk Stadler, Michael B. |
author_sort | Burger, Lukas |
collection | PubMed |
description | We have recently shown that transcription factor binding leads to defined reduction in DNA methylation, allowing for the identification of active regulatory regions from high-resolution methylomes. Here, we present MethylSeekR, a computational tool to accurately identify such footprints from bisulfite-sequencing data. Applying our method to a large number of published human methylomes, we demonstrate its broad applicability and generalize our previous findings from a neuronal differentiation system to many cell types and tissues. MethylSeekR is available as an R package at www.bioconductor.org. |
format | Online Article Text |
id | pubmed-3763559 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-37635592013-09-10 Identification of active regulatory regions from DNA methylation data Burger, Lukas Gaidatzis, Dimos Schübeler, Dirk Stadler, Michael B. Nucleic Acids Res Methods Online We have recently shown that transcription factor binding leads to defined reduction in DNA methylation, allowing for the identification of active regulatory regions from high-resolution methylomes. Here, we present MethylSeekR, a computational tool to accurately identify such footprints from bisulfite-sequencing data. Applying our method to a large number of published human methylomes, we demonstrate its broad applicability and generalize our previous findings from a neuronal differentiation system to many cell types and tissues. MethylSeekR is available as an R package at www.bioconductor.org. Oxford University Press 2013-09 2013-07-04 /pmc/articles/PMC3763559/ /pubmed/23828043 http://dx.doi.org/10.1093/nar/gkt599 Text en © The Author(s) 2013. Published by Oxford University Press. http://creativecommons.org/licenses/by/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Methods Online Burger, Lukas Gaidatzis, Dimos Schübeler, Dirk Stadler, Michael B. Identification of active regulatory regions from DNA methylation data |
title | Identification of active regulatory regions from DNA methylation data |
title_full | Identification of active regulatory regions from DNA methylation data |
title_fullStr | Identification of active regulatory regions from DNA methylation data |
title_full_unstemmed | Identification of active regulatory regions from DNA methylation data |
title_short | Identification of active regulatory regions from DNA methylation data |
title_sort | identification of active regulatory regions from dna methylation data |
topic | Methods Online |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3763559/ https://www.ncbi.nlm.nih.gov/pubmed/23828043 http://dx.doi.org/10.1093/nar/gkt599 |
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