A case study for cloud based high throughput analysis of NGS data using the globus genomics system

Area of Science:

• Genomics
• Bioinformatics
• Computational Biology

Background:

• Next generation sequencing (NGS) technologies generate vast datasets.
• Handling and analyzing NGS data requires significant computational infrastructure and specialized bioinformatics expertise.
• Existing solutions often struggle with the scale and complexity of terabyte-sized genomic data.

Purpose of the Study:

• To present a practical solution for managing and analyzing large-scale NGS data.
• To introduce Globus Genomics as a service simplifying NGS data handling and analysis.
• To address the end-to-end NGS analysis requirements in translational genomics.

Main Methods:

• Implementation of Globus Genomics, an enhanced Galaxy workflow system.
• Leveraging Amazon's cloud computing infrastructure for elastic scaling and parallel processing.
• Development of a service-based platform for easy, reliable, and fast data processing and transfer.

Main Results:

• Successful simplification of terabyte-scale data handling for NGS.
• Provision of advanced tools for comprehensive NGS data analysis.
• Enabled parallel execution of multiple workflows to meet scale-out analysis needs.

Conclusions:

• Globus Genomics provides a robust and scalable solution for NGS data challenges.
• The system facilitates efficient translational genomics research by simplifying data analysis.
• Cloud-based infrastructure is crucial for addressing the computational demands of modern genomics.