An architecture for genomics analysis in a clinical setting using Galaxy and Docker

Area of Science:

• Bioinformatics
• Computational Biology
• Clinical Diagnostics

Background:

• Next-generation sequencing (NGS) is vital for molecular diagnostics and personalized medicine.
• Clinical bioinformatics workflows require robust reproducibility and traceability.
• Existing platforms can be complex to deploy and manage.

Purpose of the Study:

• To develop an integrated bioinformatics platform for clinical applications.
• To enhance the ease of use and reproducibility of molecular data analysis.
• To improve traceability of analytical actions in a clinical setting.

Main Methods:

• Utilized Docker container technology for tool isolation and versioning.
• Integrated the Galaxy open-source bioinformatics platform.
• Developed AnalysisManager for simplified, single-click analyses.
• Incorporated a Shiny/R environment for interactive data visualization.
• Implemented ReGaTe for data traceability linked to EDAM ontology.

Main Results:

• Successfully deployed a simplified, small-size analytical platform.
• Enabled isolated and versioned bioinformatics tools via Docker images.
• Achieved single-click analysis for biologists through AnalysisManager.
• Ensured data traceability by recording analytical actions and linking inputs/outputs.
• Provided an interactive environment for output visualization.

Conclusions:

• The Docker and Galaxy-based platform simplifies clinical bioinformatics.
• The solution enhances reproducibility and traceability in molecular diagnostics.
• This approach facilitates personalized treatment selection through robust data analysis.