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Related Experiment Video

Updated: May 9, 2026

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine

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Published on: December 22, 2017

GRAPEVNE - Graphical Analytical Pipeline Development Environment for Infectious Diseases.

John-Stuart Brittain^1,2, Joseph Tsui^2,3, Rhys Inward^2,3

¹Oxford Research Software Engineering Group, University of Oxford, Oxford, England, UK.

Wellcome Open Research

|June 30, 2025

Summary

This summary is machine-generated.

GRAPEVNE simplifies infectious disease data analysis with modular pipelines for real-time public health insights and pandemic preparedness. This platform enhances data-driven discovery and reproducibility in research.

Keywords:

automated workflows data science epidemiology genomics graphical interface open-source outbreaks snakemake

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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.