The technology behind TB DEPOT: a novel public analytics platform
integrating tuberculosis clinical,genomic, and radiological data for visual and
statistical exploration |
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Authors: | Alyssa Long Alexander Glogowski Matthew Meppiel Lisa De Vito Eric Engle Michael Harris Grace Ha Darren Schneider Andrei Gabrielian Darrell E Hurt Alex Rosenthal |
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Affiliation: | Department of Health and Human Services, Office of Cyber Infrastructure and Computational Biology, National Institute of Allergy and Infectious Diseases National Institutes of Health, Bethesda, Maryland, USA |
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Abstract: | ObjectiveClinical research informatics tools are necessary to support comprehensive studies of infectious diseases. The National Institute of Allergy and Infectious Diseases (NIAID) developed the publicly accessible Tuberculosis Data Exploration Portal (TB DEPOT) to address the complex etiology of tuberculosis (TB).Materials and MethodsTB DEPOT displays deidentified patient case data and facilitates analyses across a wide range of clinical, socioeconomic, genomic, and radiological factors. The solution is built using Amazon Web Services cloud-based infrastructure, .NET Core, Angular, Highcharts, R, PLINK, and other custom-developed services. Structured patient data, pathogen genomic variants, and medical images are integrated into the solution to allow seamless filtering across data domains.ResultsResearchers can use TB DEPOT to query TB patient cases, create and save patient cohorts, and execute comparative statistical analyses on demand. The tool supports user-driven data exploration and fulfills the National Institute of Health’s Findable, Accessible, Interoperable, and Reusable (FAIR) principles.DiscussionTB DEPOT is the first tool of its kind in the field of TB research to integrate multidimensional data from TB patient cases. Its scalable and flexible architectural design has accommodated growth in the data, organizations, types of data, feature requests, and usage. Use of client-side technologies over server-side technologies and prioritizing maintenance have been important lessons learned. Future directions are dynamically prioritized and key functionality is shared through an application programming interface.ConclusionThis paper describes the platform development methodology, resulting functionality, benefits, and technical considerations of a clinical research informatics application to support increased understanding of TB. |
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Keywords: | clinical research informatics tuberculosis cohort creation data analysis data integration |
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