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NCBI's Virus Discovery Codeathon: Building "FIVE" -The Federated Index of Viral Experiments API Index
Joan Martí-Carreras1, Alejandro Rafael Gener2,3,4,5, Sierra D Miller6
1Laboratory of Clinical and Epidemiological Virology, KU Leuven Department of Microbiology, Immunology and Transplantation, Rega Institute, Leuven BE3000, Belgium.
Viruses
|December 16, 2020
Summary
A new federated index of viral experiments (FIVE) was developed to unify virus data, addressing annotation inconsistencies. This tool integrates genomic data and variation, improving accessibility for researchers studying viral diversity.
Area of Science:
- Bioinformatics
- Virology
- Data Science
Background:
- Decentralized viral sequence data leads to annotation inconsistencies and lack of consensus.
- Unifying and comparing diverse viral annotations is crucial for both established and emerging research communities.
Purpose of the Study:
- To develop an integrated and federated viral index to address data fragmentation and annotation challenges.
- To create a comprehensive resource for viral functional and taxonomic annotations, including virus-host pairings and genomic variation.
Main Methods:
- Development of the Federated Index of Viral Experiments (FIVE) during the Virus Hunting Toolkit codeathon (VHT-2).
- Integration of pre-existing and novel annotations, virus-host pairings, and viral genome diversity graphs (proof-of-concept for HIV).
- Implementation using Google BigQuery for efficient data access and development of a Python API for enhanced querying.
Main Results:
- FIVE successfully integrates diverse viral annotations and virus-host data, creating a unified resource.
- The index incorporates viral genome variation, exemplified by HIV diversity graphs, a novel feature for virus databases.
- FIVE is the first virus-specific federated index of its kind, publicly accessible via a Python API.
Conclusions:
- The Federated Index of Viral Experiments (FIVE) provides a scalable and accessible solution for unifying viral data.
- Incorporating genomic variation enhances the representation of viral diversity in biological databases.
- The developed Python API significantly improves data accessibility and query capabilities for viral research.
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