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      MethSMRT: an integrative database for DNA N6-methyladenine and N4-methylcytosine generated by single-molecular real-time sequencing

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          Abstract

          DNA methylation is an important type of epigenetic modifications, where 5- methylcytosine (5mC), 6-methyadenine (6mA) and 4-methylcytosine (4mC) are the most common types. Previous efforts have been largely focused on 5mC, providing invaluable insights into epigenetic regulation through DNA methylation. Recently developed single-molecule real-time (SMRT) sequencing technology provides a unique opportunity to detect the less studied DNA 6mA and 4mC modifications at single-nucleotide resolution. With a rapidly increased amount of SMRT sequencing data generated, there is an emerging demand to systematically explore DNA 6mA and 4mC modifications from these data sets. MethSMRT is the first resource hosting DNA 6mA and 4mC methylomes. All the data sets were processed using the same analysis pipeline with the same quality control. The current version of the database provides a platform to store, browse, search and download epigenome-wide methylation profiles of 156 species, including seven eukaryotes such as Arabidopsis, C. elegans, Drosophila, mouse and yeast, as well as 149 prokaryotes. It also offers a genome browser to visualize the methylation sites and related information such as single nucleotide polymorphisms (SNP) and genomic annotation. Furthermore, the database provides a quick summary of statistics of methylome of 6mA and 4mC and predicted methylation motifs for each species. MethSMRT is publicly available at http://sysbio.sysu.edu.cn/methsmrt/ without use restriction.

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          The Gene Expression Omnibus Database.

          The Gene Expression Omnibus (GEO) database is an international public repository that archives and freely distributes high-throughput gene expression and other functional genomics data sets. Created in 2000 as a worldwide resource for gene expression studies, GEO has evolved with rapidly changing technologies and now accepts high-throughput data for many other data applications, including those that examine genome methylation, chromatin structure, and genome-protein interactions. GEO supports community-derived reporting standards that specify provision of several critical study elements including raw data, processed data, and descriptive metadata. The database not only provides access to data for tens of thousands of studies, but also offers various Web-based tools and strategies that enable users to locate data relevant to their specific interests, as well as to visualize and analyze the data. This chapter includes detailed descriptions of methods to query and download GEO data and use the analysis and visualization tools. The GEO homepage is at http://www.ncbi.nlm.nih.gov/geo/.
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            JBrowse: a dynamic web platform for genome visualization and analysis

            Background JBrowse is a fast and full-featured genome browser built with JavaScript and HTML5. It is easily embedded into websites or apps but can also be served as a standalone web page. Results Overall improvements to speed and scalability are accompanied by specific enhancements that support complex interactive queries on large track sets. Analysis functions can readily be added using the plugin framework; most visual aspects of tracks can also be customized, along with clicks, mouseovers, menus, and popup boxes. JBrowse can also be used to browse local annotation files offline and to generate high-resolution figures for publication. Conclusions JBrowse is a mature web application suitable for genome visualization and analysis.
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              The genome portal of the Department of Energy Joint Genome Institute: 2014 updates

              The U.S. Department of Energy (DOE) Joint Genome Institute (JGI), a national user facility, serves the diverse scientific community by providing integrated high-throughput sequencing and computational analysis to enable system-based scientific approaches in support of DOE missions related to clean energy generation and environmental characterization. The JGI Genome Portal (http://genome.jgi.doe.gov) provides unified access to all JGI genomic databases and analytical tools. The JGI maintains extensive data management systems and specialized analytical capabilities to manage and interpret complex genomic data. A user can search, download and explore multiple data sets available for all DOE JGI sequencing projects including their status, assemblies and annotations of sequenced genomes. Here we describe major updates of the Genome Portal in the past 2 years with a specific emphasis on efficient handling of the rapidly growing amount of diverse genomic data accumulated in JGI.
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                04 January 2017
                18 October 2016
                18 October 2016
                : 45
                : Database issue , Database issue
                : D85-D89
                Affiliations
                [1 ]State Key Laboratory of Ophthalmology, Guangdong Provincial Key Lab of Ophthalmology and Visual Science, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou 510060, China
                [2 ]Center for Precision Medicine, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University, Guangzhou 510000, China
                [3 ]Collaborative Innovation Center of Genetics and Development, Fudan University, Shanghai 200438, China
                Author notes
                [* ]To whom correspondence should be addressed. Tel: +86 20 87335131; Email: xiezhi@ 123456gmail.com
                Correspondence may also be addressed to Chuanle Xiao. Tel: +86 20 87335131; Email: xiaochuanle@ 123456126.com
                []These authors contributed equally to this work as the first authors.
                Article
                10.1093/nar/gkw950
                5210644
                27924023
                76486011-7006-4b4e-bbfc-4f20beff1589
                © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

                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@ 123456oup.com

                History
                : 10 October 2016
                : 30 September 2016
                : 11 August 2016
                Page count
                Pages: 5
                Categories
                Database Issue
                Custom metadata
                04 January 2017

                Genetics
                Genetics

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