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Uncovering Host-microbiome Interactions in Global Systems with Collaborative Programming: A Novel Approach Integrating Social and Data Sciences [version 1; peer review: awaiting peer review]
F1000Research
  • Jenna Oberstaller, University of South Florida
  • Swamy Rakesh Adapa, University of South Florida
  • Guy Dayhoff, II, University of South Florida
  • Justin Gibbons, University of South Florida
  • Gregory S. Herbert, University of South Florida
Document Type
Article
Publication Date
1-1-2020
Keywords
  • hackathon,
  • codeathon,
  • data science,
  • transdisciplinary,
  • gut microbiome,
  • oral microbiome,
  • human migration microbiome,
  • Clinical Informatics,
  • Bioinformatics,
  • Operational Taxonomic Unit (OTU),
  • 16S rRNA,
  • machine learning,
  • Geographic Information Systems (GIS)
Digital Object Identifier (DOI)
https://doi.org/10.12688/f1000research.26459.1
Disciplines
Abstract

Microbiome data are undergoing exponential growth powered by rapid technological advancement. As the scope and depth of microbiome research increases, cross-disciplinary research is urgently needed for interpreting and harnessing the unprecedented data output. However, conventional research settings pose challenges to much-needed interdisciplinary research efforts due to barriers in scientific terminologies, methodology and research-culture. To breach these barriers, our University of South Florida OneHealth Codeathon was designed to be an interactive, hands-on event that solves real-world data problems. The format brought together students, postdocs, faculty, researchers, and clinicians in a uniquely cross-disciplinary, team-focused setting. Teams were formed to encourage equitable distribution of diverse domain-experts and proficient programmers, with beginners to experts on each team. To unify the intellectual framework, we set the focus on the topics of microbiome interactions at different scales from clinical to environmental sciences, leveraging local expertise in the fields of genetics, genomics, clinical data, and social and geospatial sciences. As a result, teams developed working methods and pipelines to face major challenges in current microbiome research, including data integration, experimental power calculations, geospatial mapping, and machine-learning classifiers. This broad, transdisciplinary and efficient workflow will be an example for future workshops to deliver useful data-science products.

Comments

Full list of authors: Jenna Oberstaller, Swamy Rakesh Adapa, Guy W. Dayhoff II, Justin Gibbons, Thomas E. Keller, Chang Li, Jean Lim, Minh Pham, Anujit Sarkar, Ravi Sharma, Agaz H. Wani, Andrea Vianello, Linh M. Duong, Chenggi Wang, Celine Grace F. Atkinson, Madeleine Barrow, Nathan W. Van Bibber, Jan Dahrendorff, David A. E. Dean, Omkar Dokur, Gloria C. Ferreira, Mitchell Hastings, Gregory S. Herbert, Khandaker Tasnim Huq, Youngchul Kim, Xiangyun Liao, XiaoMing Liu, Fahad Mansuri, Lynn B. Martin, Elizabeth M. Miller, Ojas Natarajan, Jinyong Pang, Francesca Prieto, Peter W. Radulovic, Vyoma Sheth, Matthew Sumpter, Desirae Sutherland, Nisha Vijayakumar, Rays H. Y. Jiang

Rights Information
Creative Commons Attribution 4.0
Citation / Publisher Attribution

F1000Research, v. 9, art. 1478

Citation Information
Jenna Oberstaller, Swamy Rakesh Adapa, Guy Dayhoff, Justin Gibbons, et al.. "Uncovering Host-microbiome Interactions in Global Systems with Collaborative Programming: A Novel Approach Integrating Social and Data Sciences [version 1; peer review: awaiting peer review]" F1000Research Vol. 9 (2020)
Available at: http://works.bepress.com/gregory-herbert/45/