Overview and data flow


NGSmethDB stores whole genome methylomes generated from short-read datasets 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 development of methylation epimarkers: 1) differentially methylated single‑cytosines; and 2) 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 the comparison of different samples. Besides conventional database dumps, standard track hubs were implemented, which improved database access and visualization in Genome Browsers. An NGSmethDB API server was also implemented, thus giving access to the entire database via a RESTful API. A Python client and a multiplatform virtual machine allow now for program-driven access to NGSmethDB data from user desktop. This way, private methylation data can be compared to NGSmethDB data without the need to upload it to public servers

How to cite

[1] Stefanie Geisen, Guillermo Barturen, Ángel M. Alganza, Michael Hackenberg and José L. Oliver. 2014. NGSmethDB: an updated genome resource for high quality, single-cytosine resolution methylomes. Nucl. Acids Res. (1 January 2014) 42 (D1): D53-D59 first published online November 22, 2013
doi:10.1093/nar/gkt1202, PMID: 24271385
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[2] Michael Hackenberg, Guillermo Barturen and José L. Oliver. 2010. NGSmethDB: A database for next-generation sequencing single-cytosine-resolution DNA methylation data. Nucleic Acids Research, 2010, 1–5
http://dx.doi.org/10.1093/nar/gkq942, PMID: 20965971
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