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Experiences Building Globus Genomics: A Next-Generation Sequencing Analysis Service using Galaxy, Globus, and Amazon
Ravi K Madduri1, Dinanath Sulakhe1, Lukasz Lacinski1
1Computation Institute University of Chicago and Argonne National Laboratory Chicago, IL.
Globus Genomics offers automated analysis of next-generation sequencing (NGS) genomic data. This system enables rapid, large-scale data processing for researchers without local infrastructure.
Area of Science:
- Bioinformatics
- Computational Biology
- Genomic Data Analysis
Background:
- Next-generation sequencing (NGS) generates vast amounts of genomic data.
- Analyzing large genomic datasets requires significant computational resources and expertise.
- Current analysis methods can be time-consuming and require local infrastructure.
Purpose of the Study:
- To present Globus Genomics, an automated system for rapid analysis of large-scale NGS data.
- To enable biomedical researchers to analyze genomic data without local computing infrastructure or software installation.
- To demonstrate the performance and cost-effectiveness of the Globus Genomics system.
Main Methods:
- End-to-end automation of data analysis stages.
- Integration of Globus file transfer for data retrieval.
- Utilization of Galaxy for workflow management.
- Leveraging Amazon EC2 for elastic resource provisioning.
- HTCondor for efficient pipeline scheduling.
Main Results:
- Successful implementation of a fully automated NGS data analysis system.
- Demonstrated rapid analysis of large genomic datasets.
- Reported performance and cost metrics for representative workloads.
- Enabled researchers to bypass local infrastructure requirements.
Conclusions:
- Globus Genomics provides a scalable and automated solution for NGS data analysis.
- The system empowers biomedical researchers with efficient and accessible genomic data processing capabilities.
- This approach reduces barriers to entry for complex genomic data analysis.
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