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NGSmethDB 2017: enhanced methylomes and differential methylation

The 2017 update of NGSmethDB stores whole genome methylomes generated from short-read data sets obtained by bisulfite sequencing (WGBS) technology. To generate high-quality methylomes, stringent quality controls were integrated with third-part software, adding also a two-step mapping process to expl...

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Autores principales: Lebrón, Ricardo, Gómez-Martín, Cristina, Carpena, Pedro, Bernaola-Galván, Pedro, Barturen, Guillermo, Hackenberg, Michael, Oliver, José L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5210667/
https://www.ncbi.nlm.nih.gov/pubmed/27794041
http://dx.doi.org/10.1093/nar/gkw996
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author Lebrón, Ricardo
Gómez-Martín, Cristina
Carpena, Pedro
Bernaola-Galván, Pedro
Barturen, Guillermo
Hackenberg, Michael
Oliver, José L.
author_facet Lebrón, Ricardo
Gómez-Martín, Cristina
Carpena, Pedro
Bernaola-Galván, Pedro
Barturen, Guillermo
Hackenberg, Michael
Oliver, José L.
author_sort Lebrón, Ricardo
collection PubMed
description The 2017 update of NGSmethDB stores whole genome methylomes generated from short-read data sets obtained by bisulfite sequencing (WGBS) technology. To generate high-quality methylomes, stringent quality controls were integrated with third-part software, adding also a two-step mapping process to exploit the advantages of the new genome assembly models. The samples were all profiled under constant parameter settings, thus enabling comparative downstream analyses. Besides a significant increase in the number of samples, NGSmethDB now includes two additional data-types, which are a valuable resource for the discovery of methylation epigenetic biomarkers: (i) differentially methylated single-cytosines; and (ii) methylation segments (i.e. genome regions of homogeneous methylation). The NGSmethDB back-end is now based on MongoDB, a NoSQL hierarchical database using JSON-formatted documents and dynamic schemas, thus accelerating sample comparative analyses. Besides conventional database dumps, track hubs were implemented, which improved database access, visualization in genome browsers and comparative analyses to third-part annotations. In addition, the database can be also accessed through a RESTful API. Lastly, a Python client and a multiplatform virtual machine allow for program-driven access from user desktop. This way, private methylation data can be compared to NGSmethDB without the need to upload them to public servers. Database website: http://bioinfo2.ugr.es/NGSmethDB.
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spelling pubmed-52106672017-01-05 NGSmethDB 2017: enhanced methylomes and differential methylation Lebrón, Ricardo Gómez-Martín, Cristina Carpena, Pedro Bernaola-Galván, Pedro Barturen, Guillermo Hackenberg, Michael Oliver, José L. Nucleic Acids Res Database Issue The 2017 update of NGSmethDB stores whole genome methylomes generated from short-read data sets obtained by bisulfite sequencing (WGBS) technology. To generate high-quality methylomes, stringent quality controls were integrated with third-part software, adding also a two-step mapping process to exploit the advantages of the new genome assembly models. The samples were all profiled under constant parameter settings, thus enabling comparative downstream analyses. Besides a significant increase in the number of samples, NGSmethDB now includes two additional data-types, which are a valuable resource for the discovery of methylation epigenetic biomarkers: (i) differentially methylated single-cytosines; and (ii) methylation segments (i.e. genome regions of homogeneous methylation). The NGSmethDB back-end is now based on MongoDB, a NoSQL hierarchical database using JSON-formatted documents and dynamic schemas, thus accelerating sample comparative analyses. Besides conventional database dumps, track hubs were implemented, which improved database access, visualization in genome browsers and comparative analyses to third-part annotations. In addition, the database can be also accessed through a RESTful API. Lastly, a Python client and a multiplatform virtual machine allow for program-driven access from user desktop. This way, private methylation data can be compared to NGSmethDB without the need to upload them to public servers. Database website: http://bioinfo2.ugr.es/NGSmethDB. Oxford University Press 2017-01-04 2016-10-27 /pmc/articles/PMC5210667/ /pubmed/27794041 http://dx.doi.org/10.1093/nar/gkw996 Text en © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution 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 Database Issue
Lebrón, Ricardo
Gómez-Martín, Cristina
Carpena, Pedro
Bernaola-Galván, Pedro
Barturen, Guillermo
Hackenberg, Michael
Oliver, José L.
NGSmethDB 2017: enhanced methylomes and differential methylation
title NGSmethDB 2017: enhanced methylomes and differential methylation
title_full NGSmethDB 2017: enhanced methylomes and differential methylation
title_fullStr NGSmethDB 2017: enhanced methylomes and differential methylation
title_full_unstemmed NGSmethDB 2017: enhanced methylomes and differential methylation
title_short NGSmethDB 2017: enhanced methylomes and differential methylation
title_sort ngsmethdb 2017: enhanced methylomes and differential methylation
topic Database Issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5210667/
https://www.ncbi.nlm.nih.gov/pubmed/27794041
http://dx.doi.org/10.1093/nar/gkw996
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