A cloud-based bioinformatic analytic infrastructure and Data Management Core for the Expanded Program on Immunization Consortium.

Sofia M Vignolo ORCID logo; Joann Diray-Arce ORCID logo; Kerry McEnaney; Shun Rao; Casey P Shannon ORCID logo; Olubukola T Idoko ORCID logo; Fatoumata Cole; Alansana Darboe ORCID logo; Fatoumatta Cessay; Rym Ben-Othman ORCID logo; +4 more... Scott J Tebbutt ORCID logo; Beate Kampmann ORCID logo; Ofer Levy ORCID logo; Al Ozonoff ORCID logo; (2020) A cloud-based bioinformatic analytic infrastructure and Data Management Core for the Expanded Program on Immunization Consortium. Journal of clinical and translational science, 5 (1). e52-. ISSN 2059-8661 DOI: 10.1017/cts.2020.546
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The Expanded Program for Immunization Consortium - Human Immunology Project Consortium study aims to employ systems biology to identify and characterize vaccine-induced biomarkers that predict immunogenicity in newborns. Key to this effort is the establishment of the Data Management Core (DMC) to provide reliable data and bioinformatic infrastructure for centralized curation, storage, and analysis of multiple de-identified "omic" datasets. The DMC established a cloud-based architecture using Amazon Web Services to track, store, and share data according to National Institutes of Health standards. The DMC tracks biological samples during collection, shipping, and processing while capturing sample metadata and associated clinical data. Multi-omic datasets are stored in access-controlled Amazon Simple Storage Service (S3) for data security and file version control. All data undergo quality control processes at the generating site followed by DMC validation for quality assurance. The DMC maintains a controlled computing environment for data analysis and integration. Upon publication, the DMC deposits finalized datasets to public repositories. The DMC architecture provides resources and scientific expertise to accelerate translational discovery. Robust operations allow rapid sharing of results across the project team. Maintenance of data quality standards and public data deposition will further benefit the scientific community.


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