TB DEPOT (Data Exploration Portal): A multi-domain tuberculosis data analysis resource

PLoS One. 2019 May 23;14(5):e0217410. doi: 10.1371/journal.pone.0217410. eCollection 2019.

Abstract

The NIAID TB Portals Program (TBPP) established a unique and growing database repository of socioeconomic, geographic, clinical, laboratory, radiological, and genomic data from patient cases of drug-resistant tuberculosis (DR-TB). Currently, there are 2,428 total cases from nine country sites (Azerbaijan, Belarus, Moldova, Georgia, Romania, China, India, Kazakhstan, and South Africa), 1,611 (66%) of which are multidrug- or extensively-drug resistant and 1,185 (49%), 863 (36%), and 952 (39%) of which contain X-ray, computed tomography (CT) scan, and genomic data, respectively. We introduce the Data Exploration Portal (TB DEPOT, https://depot.tbportals.niaid.nih.gov) to visualize and analyze these multi-domain data. The TB DEPOT leverages the TBPP integration of clinical, socioeconomic, genomic, and imaging data into standardized formats and enables user-driven, repeatable, and reproducible analyses. It furthers the TBPP goals to provide a web-enabled analytics platform to countries with a high burden of multidrug-resistant TB (MDR-TB) but limited IT resources and inaccessible data, and enables the reusability of data, in conformity with the NIH's Findable, Accessible, Interoperable, and Reusable (FAIR) principles. TB DEPOT provides access to "analysis-ready" data and the ability to generate and test complex clinically-oriented hypotheses instantaneously with minimal statistical background and data processing skills. TB DEPOT is also promising for enhancing medical training and furnishing well annotated, hard to find, MDR-TB patient cases. TB DEPOT, as part of TBPP, further fosters collaborative research efforts to better understand drug-resistant tuberculosis and aid in the development of novel diagnostics and personalized treatment regimens.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Big Data
  • Cohort Studies
  • Data Analysis
  • Databases, Factual*
  • Drug Resistance, Multiple, Bacterial / genetics
  • Genome, Bacterial
  • Humans
  • Mycobacterium tuberculosis / drug effects
  • Mycobacterium tuberculosis / genetics
  • National Institute of Allergy and Infectious Diseases (U.S.)
  • Polymorphism, Single Nucleotide
  • Tuberculosis, Multidrug-Resistant* / diagnostic imaging
  • Tuberculosis, Multidrug-Resistant* / drug therapy
  • Tuberculosis, Multidrug-Resistant* / microbiology
  • United States
  • Web Browser

Grants and funding

This project has been funded in part with Federal funds from the National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of Health, Department of Health and Human Services under BCBB Support Services Contract HHSN316201300006W/HHSN27200002 to MSC, Inc; U.S. Civilian Research and Development Foundation (“CDRF”) Agreement No. BOB1-31120-MK-13; and the International Science and Technology Center. The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the NIH. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.