Uncovering host-microbiome interactions in global systems with collaborative programming: a novel approach integrating social and data sciences [version 1; peer review: 1 approved with reservations]

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.