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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...

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Detalles Bibliográficos
Autores principales: Burger, Lukas, Gaidatzis, Dimos, Schübeler, Dirk, Stadler, Michael B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2013
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.
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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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