Towards an open analysis ecosystem for Plasmodium genomic epidemiology

Area of Science:

• Genomic Epidemiology
• Bioinformatics
• Malaria Control

Background:

• Advances in Plasmodium sequencing and bioinformatics provide valuable malaria epidemiological insights.
• Translating genomic data into actionable information for decision-makers and national malaria control programs faces significant challenges.
• Barriers hinder the integration of genomic advances into a functional data analysis ecosystem for standardized, interpretable results.

Purpose of the Study:

• To address challenges in translating Plasmodium genomic data into actionable information for malaria control.
• To identify available analysis tools, evaluate software standards, improve documentation, and outline workflows for genomic data analysis.
• To establish a community resource for malaria genomic data analysis.

Main Methods:

• Convened 18 experts from 15 institutions at the Reproducibility, Accessibility, Documentation, and Interoperability Standards Hackathon (RADISH23).
• Identified eight genomic data use cases and developed them into analysis workflows.
• Mapped 40 identified Plasmodium genomic analysis tools against workflow functionalities, prioritizing 22 for software standards evaluation.
• Developed objective criteria for evaluating software standards and created tutorials for 10 tools.

Main Results:

• Eight genomic data use cases were identified and developed into modular analysis workflows.
• A set of objective criteria for evaluating software standards was established.
• Forty Plasmodium genomic analysis tools were identified, with 22 prioritized for evaluation.
• 10 tools received additional tutorials with reproducible code and shared datasets.
• PGEforge (mrc-ide.github.io/PGEforge) was launched as a central, open repository for malaria genomic data analysis resources.

Conclusions:

• Standardized workflows and objective evaluation criteria are crucial for translating Plasmodium genomic data into practical tools for malaria control.
• The developed resources and PGEforge repository facilitate a modular approach to genomic data analysis, supporting national malaria control programs.
• Continued community engagement and resource sharing via PGEforge are essential for advancing malaria genomic epidemiology.