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NCBI's Virus Discovery Codeathon: Building "FIVE" -The Federated Index of Viral Experiments API Index.

Authors:
Joan Martí-Carreras Alejandro Rafael Gener Sierra D Miller Anderson F Brito Christiam E Camacho Ryan Connor Ward Deboutte Cody Glickman David M Kristensen Wynn K Meyer Sejal Modha Alexis L Norris Surya Saha Anna K Belford Evan Biederstedt James Rodney Brister Jan P Buchmann Nicholas P Cooley Robert A Edwards Kiran Javkar Michael Muchow Harihara Subrahmaniam Muralidharan Charles Pepe-Ranney Nidhi Shah Migun Shakya Michael J Tisza Benjamin J Tully Bert Vanmechelen Valerie C Virta Jake L Weissman Vadim Zalunin Alexandre Efremov Ben Busby

Viruses 2020 12 10;12(12). Epub 2020 Dec 10.

National Center for Biotechnology Information, U.S. National Library of Medicine, National Institutes of Health, 9000 Rockville Pike, Bethesda, MD 20894, USA.

Viruses represent important test cases for data federation due to their genome size and the rapid increase in sequence data in publicly available databases. However, some consequences of previously decentralized (unfederated) data are lack of consensus or comparisons between feature annotations. Unifying or displaying alternative annotations should be a priority both for communities with robust entry representation and for nascent communities with burgeoning data sources. To this end, during this three-day continuation of the Virus Hunting Toolkit codeathon series (VHT-2), a new integrated and federated viral index was elaborated. This Federated Index of Viral Experiments (FIVE) integrates pre-existing and novel functional and taxonomy annotations and virus-host pairings. Variability in the context of viral genomic diversity is often overlooked in virus databases. As a proof-of-concept, FIVE was the first attempt to include viral genome variation for HIV, the most well-studied human pathogen, through viral genome diversity graphs. As per the publication of this manuscript, FIVE is the first implementation of a virus-specific federated index of such scope. FIVE is coded in BigQuery for optimal access of large quantities of data and is publicly accessible. Many projects of database or index federation fail to provide easier alternatives to access or query information. To this end, a Python API query system was developed to enhance the accessibility of FIVE.

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http://dx.doi.org/10.3390/v12121424DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7764237PMC
December 2020

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NCBI's Virus Discovery Codeathon: Building "FIVE" -The Federated Index of Viral Experiments API Index.

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