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

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 pr...

Full description

Bibliographic Details
Main Authors: Sofia M. Vignolo, Joann Diray-Arce, Kerry McEnaney, Shun Rao, Casey P. Shannon, Olubukola T. Idoko, Fatoumata Cole, Alansana Darboe, Fatoumatta Cessay, Rym Ben-Othman, EPIC Consortium, Scott J. Tebbutt, Beate Kampmann, Ofer Levy, Al Ozonoff
Format: Article
Language:English
Published: Cambridge University Press 2021-01-01
Series:Journal of Clinical and Translational Science
Subjects:
Online Access:https://www.cambridge.org/core/product/identifier/S2059866120005464/type/journal_article
Description
Summary: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.
ISSN:2059-8661