GRAPEVNE - Graphical Analytical Pipeline Development Environment for Infectious Diseases

Area of Science:

• Computational Biology
• Epidemiology
• Bioinformatics

Background:

• Increasing infectious disease data volume and diversity offer opportunities for real-time public health decision-making.
• Global data utilization is hindered by preprocessing, data science capacity, and resource access disparities.

Purpose of the Study:

• To develop a platform facilitating local-level, large-scale infectious disease data analysis without cross-border data sharing.
• To streamline the creation, execution, and sharing of complex, repetitive data analysis workflows.

Main Methods:

• Developed GRAPEVNE (Graphical Analytical Pipeline Development Environment), a platform using the Snakemake workflow management system.
• Implemented a modular pipeline approach where each module is a self-contained Snakemake workflow.
• Ensured interoperability through configurations, scripts, and metadata within each module.

Main Results:

• GRAPEVNE supports diverse applications including genomic analysis, epidemiological modeling, and large-scale data processing.
• The platform simplifies complex workflows, fostering data-driven discovery and enhancing research reproducibility.
• Demonstrated end-to-end automation with a dengue virus pipeline for phylogenetic analysis and phylogeographic inference.

Conclusions:

• GRAPEVNE empowers researchers and public health institutions by simplifying infectious disease data analysis.
• The open-source, modular platform enhances real-time outbreak monitoring, forecasting, and epidemiological data processing.
• Facilitates continuous innovation in biomedical and epidemiological research through a user-driven ecosystem.