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The technology behind TB DEPOT: a novel public analytics platform integrating tuberculosis clinical, genomic, and radiological data for visual and statistical exploration

OBJECTIVE: Clinical 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...

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Autores principales: Long, Alyssa, Glogowski, Alexander, Meppiel, Matthew, De Vito, Lisa, Engle, Eric, Harris, Michael, Ha, Grace, Schneider, Darren, Gabrielian, Andrei, Hurt, Darrell E, Rosenthal, Alex
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8454519/
https://www.ncbi.nlm.nih.gov/pubmed/33150354
http://dx.doi.org/10.1093/jamia/ocaa228
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author Long, Alyssa
Glogowski, Alexander
Meppiel, Matthew
De Vito, Lisa
Engle, Eric
Harris, Michael
Ha, Grace
Schneider, Darren
Gabrielian, Andrei
Hurt, Darrell E
Rosenthal, Alex
author_facet Long, Alyssa
Glogowski, Alexander
Meppiel, Matthew
De Vito, Lisa
Engle, Eric
Harris, Michael
Ha, Grace
Schneider, Darren
Gabrielian, Andrei
Hurt, Darrell E
Rosenthal, Alex
author_sort Long, Alyssa
collection PubMed
description OBJECTIVE: Clinical 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 METHODS: TB 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. RESULTS: Researchers 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. DISCUSSION: TB 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. CONCLUSION: This 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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spelling pubmed-84545192021-09-22 The technology behind TB DEPOT: a novel public analytics platform integrating tuberculosis clinical, genomic, and radiological data for visual and statistical exploration Long, Alyssa Glogowski, Alexander Meppiel, Matthew De Vito, Lisa Engle, Eric Harris, Michael Ha, Grace Schneider, Darren Gabrielian, Andrei Hurt, Darrell E Rosenthal, Alex J Am Med Inform Assoc Research and Applications OBJECTIVE: Clinical 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 METHODS: TB 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. RESULTS: Researchers 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. DISCUSSION: TB 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. CONCLUSION: This paper describes the platform development methodology, resulting functionality, benefits, and technical considerations of a clinical research informatics application to support increased understanding of TB. Oxford University Press 2020-11-05 /pmc/articles/PMC8454519/ /pubmed/33150354 http://dx.doi.org/10.1093/jamia/ocaa228 Text en © The Author(s) 2020. Published by Oxford University Press on behalf of the American Medical Informatics Association. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research and Applications
Long, Alyssa
Glogowski, Alexander
Meppiel, Matthew
De Vito, Lisa
Engle, Eric
Harris, Michael
Ha, Grace
Schneider, Darren
Gabrielian, Andrei
Hurt, Darrell E
Rosenthal, Alex
The technology behind TB DEPOT: a novel public analytics platform integrating tuberculosis clinical, genomic, and radiological data for visual and statistical exploration
title The technology behind TB DEPOT: a novel public analytics platform integrating tuberculosis clinical, genomic, and radiological data for visual and statistical exploration
title_full The technology behind TB DEPOT: a novel public analytics platform integrating tuberculosis clinical, genomic, and radiological data for visual and statistical exploration
title_fullStr The technology behind TB DEPOT: a novel public analytics platform integrating tuberculosis clinical, genomic, and radiological data for visual and statistical exploration
title_full_unstemmed The technology behind TB DEPOT: a novel public analytics platform integrating tuberculosis clinical, genomic, and radiological data for visual and statistical exploration
title_short The technology behind TB DEPOT: a novel public analytics platform integrating tuberculosis clinical, genomic, and radiological data for visual and statistical exploration
title_sort technology behind tb depot: a novel public analytics platform integrating tuberculosis clinical, genomic, and radiological data for visual and statistical exploration
topic Research and Applications
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8454519/
https://www.ncbi.nlm.nih.gov/pubmed/33150354
http://dx.doi.org/10.1093/jamia/ocaa228
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