OSG-GEM: Gene Expression Matrix Construction Using the Open Science Grid.

Area of Science:

• Genomics
• Bioinformatics
• Computational Biology

Background:

• High-throughput DNA sequencing generates vast data, posing computational challenges for gene expression studies.
• Biologists often face limitations in accessing adequate hardware and efficient data processing workflows.
• Gene expression analysis is crucial for understanding biological processes and disease.

Purpose of the Study:

• To present OSG-GEM, a scalable, open-source Pegasus workflow designed to process high-throughput DNA sequence data.
• To enable U.S. researchers to generate gene expression matrices (GEM) using Open Science Grid (OSG) computational resources.
• To overcome hardware and workflow limitations in computational biology.

Main Methods:

• Developed a scalable, open-source Pegasus workflow named OSG-GEM.
• Utilized the Open Science Grid (OSG) for distributed high-throughput data processing.
• Assessed workflow performance, design, and accuracy in mapping sequencing reads.

Main Results:

• OSG-GEM successfully processes high-throughput DNA sequence datasets into a gene expression matrix (GEM).
• The workflow demonstrates scalability and efficient utilization of OSG computational resources.
• Accuracy assessments confirmed reliable mapping of paired-end sequencing reads to reference genomes.

Conclusions:

• OSG-GEM provides a robust solution for computational challenges in gene expression analysis.
• The workflow is accessible to researchers with Linux command-line proficiency and basic bioinformatics knowledge.
• OSG-GEM can be utilized directly on the OSG or adapted for other computing environments.