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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
Descripción
Sumario: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.