English   español  
Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/172872
logo share SHARE logo core CORE   Add this article to your Mendeley library MendeleyBASE

Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL | DATACITE
Exportar a otros formatos:


Automatic detection of genomic regions with informative epigenetic patterns

AuthorsPazos, Florencio; Garcia-Moreno, Adrian; Oliveros, Juan C.
Gene transcription regulation
Issue Date28-Nov-2018
PublisherBioMed Central
CitationBMC Genomics 19(1): 847 (2018)
Abstract[Background] Epigenetic phenomena are crucial for explaining the phenotypic plasticity seen in the cells of different tissues, developmental stages and diseases, all holding the same DNA sequence. As technology is allowing to retrieve epigenetic information in a genome-wide fashion, massive epigenomic datasets are being accumulated in public repositories. New approaches are required to mine those data to extract useful knowledge. We present here an automatic approach for detecting genomic regions with epigenetic variation patterns across samples related to a grouping of these samples, as a way of detecting regions functionally associated to the phenomenon behind the classification.
[Results] We show that the regions automatically detected by the method in the whole human genome associated to three different classifications of a set of epigenomes (cancer vs. healthy, brain vs. other organs, and fetal vs. adult tissues) are enriched in genes associated to these processes.
[Conclusions] The method is fully automatic and can exhaustively scan the whole human genome at any resolution using large collections of epigenomes as input, although it also produces good results with small datasets. Consequently, it will be valuable for obtaining functional information from the incoming epigenomic information as it continues to accumulate.
Publisher version (URL)https://doi.org/10.1186/s12864-018-5286-5
Appears in Collections:(CNB) Artículos
Files in This Item:
File Description SizeFormat 
automatic_genomics_2018.pdf2,13 MBAdobe PDFThumbnail
Show full item record
Review this work

WARNING: Items in Digital.CSIC are protected by copyright, with all rights reserved, unless otherwise indicated.