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      High-performance web services for querying gene and variant annotation

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          Abstract

          Efficient tools for data management and integration are essential for many aspects of high-throughput biology. In particular, annotations of genes and human genetic variants are commonly used but highly fragmented across many resources. Here, we describe MyGene.info and MyVariant.info, high-performance web services for querying gene and variant annotation information. These web services are currently accessed more than three million times permonth. They also demonstrate a generalizable cloud-based model for organizing and querying biological annotation information. MyGene.info and MyVariant.info are provided as high-performance web services, accessible at http://mygene.info and http://myvariant.info. Both are offered free of charge to the research community.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s13059-016-0953-9) contains supplementary material, which is available to authorized users.

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          Activities at the Universal Protein Resource (UniProt)

          emmanuel boutet, Claire O'Donovan (2014)
          The mission of the Universal Protein Resource (UniProt) (http://www.uniprot.org) is to provide the scientific community with a comprehensive, high-quality and freely accessible resource of protein sequences and functional annotation. It integrates, interprets and standardizes data from literature and numerous resources to achieve the most comprehensive catalog possible of protein information. The central activities are the biocuration of the UniProt Knowledgebase and the dissemination of these data through our Web site and web services. UniProt is produced by the UniProt Consortium, which consists of groups from the European Bioinformatics Institute (EBI), the SIB Swiss Institute of Bioinformatics (SIB) and the Protein Information Resource (PIR). UniProt is updated and distributed every 4 weeks and can be accessed online for searches or downloads.
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            Entrez Gene: gene-centered information at NCBI

            Donna R. Maglott, Jim Ostell, Kim D. Pruitt … (2004)
            Entrez Gene (www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=gene) is NCBI's database for gene-specific information. It does not include all known or predicted genes; instead Entrez Gene focuses on the genomes that have been completely sequenced, that have an active research community to contribute gene-specific information, or that are scheduled for intense sequence analysis. The content of Entrez Gene represents the result of curation and automated integration of data from NCBI's Reference Sequence project (RefSeq), from collaborating model organism databases, and from many other databases available from NCBI. Records are assigned unique, stable and tracked integers as identifiers. The content (nomenclature, map location, gene products and their attributes, markers, phenotypes, and links to citations, sequences, variation details, maps, expression, homologs, protein domains and external databases) is updated as new information becomes available. Entrez Gene is a step forward from NCBI's LocusLink, with both a major increase in taxonomic scope and improved access through the many tools associated with NCBI Entrez.
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              Mutation nomenclature extensions and suggestions to describe complex mutations: a discussion.

              J. den Dunnen, S. Antonarakis (2000)
              Consistent gene mutation nomenclature is essential for efficient and accurate reporting, testing, and curation of the growing number of disease mutations and useful polymorphisms being discovered in the human genome. While a codified mutation nomenclature system for simple DNA lesions has now been adopted broadly by the medical genetics community, it is inherently difficult to represent complex mutations in a unified manner. In this article, suggestions are presented for reporting just such complex mutations. Copyright 2000 Wiley-Liss, Inc.
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                Author and article information

                Contributors
                Andrew I. Su: asu@scripps.edu
                Chunlei Wu: cwu@scripps.edu
                Journal
                Journal ID (nlm-ta): Genome Biol
                Journal ID (iso-abbrev): Genome Biol
                Title: Genome Biology
                Publisher: BioMed Central (London )
                ISSN (Print): 1474-7596
                ISSN (Electronic): 1474-760X
                Publication date (Electronic): 6 May 2016
                Publication date PMC-release: 6 May 2016
                Publication date Collection: 2016
                Volume: 17
                Electronic Location Identifier: 91
                Affiliations
                [ ]Department of Molecular and Experimental Medicine, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037 USA
                [ ]Current address: Avera Cancer Institute, 11099 North Torrey Pines Road, La Jolla, CA 92037 USA
                [ ]Department of Biomedical Informatics and Medical Education, The University of Washington, Box SLU-BIME 358047, Seattle, WA 98195 USA
                [ ]McDonnell Genome Institute, Washington University School of Medicine, 4444 Forest Park Ave, St. Louis, MO 63108 USA
                [ ]Department of Integrative Structural and Computational Biology, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037 USA
                [ ]The Scripps Translational Science Institute, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037 USA
                [ ]Center for Research in Biological Systems, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093 USA
                [ ]Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720 USA
                Article
                Publisher ID: 953
                DOI: 10.1186/s13059-016-0953-9
                PMC ID: 4858870
                PubMed ID: 27154141
                SO-VID: 0a0b39ee-8540-42c6-a1a1-e1f00db433f0
                Copyright © © Xin et al. 2016
                License:

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                Date received : 7 January 2016
                Date accepted : 14 April 2016
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000051, National Human Genome Research Institute;
                Award ID: 1U01HG008473
                Award ID: U01HG006476
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000057, National Institute of General Medical Sciences;
                Award ID: GM083924
                Award ID: U54GM114833
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000054, National Cancer Institute;
                Award ID: K22CA188163
                Award Recipient :
                Categories
                Subject: Software
                Custom metadata
                issue-copyright-statement © The Author(s) 2016

                ScienceOpen disciplines: Genetics
                Keywords: annotation,gene,variant,api,cloud,repository,database
                Data availability:
                ScienceOpen disciplines: Genetics
                Keywords: annotation, gene, variant, api, cloud, repository, database

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