In resource-limited settings, the gap between raw genomic data and actionable public health policy is often widened by a lack of accessible, automated workflows. This demonstration showcases a reproducible bioinformatics pipeline developed to identify Antimicrobial Resistance markers within the Kenyan research ecosystem.
Leveraging open-source Linux/Bash scripting and R-based visualization, this showcase demonstrates how research software can be used to do more with less. The presenter walks through a live workflow, from processing raw sequence reads to generating diagnostic-ready reports, that has been utilized to support the One Health AMR Community Initiative. By focusing on FAIR (Findable, Accessible, Interoperable, and Reusable) software practices, this session illustrates how African researchers can lead genomic surveillance efforts without relying on expensive, proprietary platforms.
Presented at RSAfrica26 (Research Software Africa Conference), Demo/Showcase session, 27 August 2026.