ArticleNucleic acids research2017
NGSmethDB 2017: enhanced methylomes and differential methylation.
Article in Nucleic acids research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- TiSMeD: A tissue-specific methylation and expression database for biomarker and translational applications.Molecular therapy. Nucleic acids · 2026Article
- mHapBrowser: a comprehensive database for visualization and analysis of DNA methylation haplotypes.Nucleic acids research · 2024Article
- MethBank 4.0: an updated database of DNA methylation across a variety of species.Nucleic acids research · 2023Article
- Databases and prospects of dynamic gene regulation in eukaryotes: A mini review.Computational and structural biotechnology journal · 2023Review
- Computational methods and next-generation sequencing approaches to analyze epigenetics data: Profiling of methods and applications.Methods (San Diego, Calif.) · 2021Review
- MethHC 2.0: information repository of DNA methylation and gene expression in human cancer.Nucleic acids research · 2021Article
- A Method for Identification of the Methylation Level of CpG Islands From NGS Data.Scientific reports · 2020Article
- Systematics for types and effects of DNA variations.BMC genomics · 2018Review
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.