Implementing a training resource for large-scale genomic data analysis in the All of Us Researcher Workbench

Area of Science:

• Genomics
• Computational Biology
• Bioinformatics

Background:

• Genomic research faces barriers due to underrepresentation and limited computational training.
• The All of Us Research Program offers a diverse dataset but requires skilled researchers for analysis.
• Early-career researchers need accessible training to utilize large-scale genetic data.

Purpose of the Study:

• To address the lack of representation and computational training in genomic research.
• To equip early-career researchers with skills for analyzing the All of Us dataset.
• To foster innovation in precision medicine and advance equity in genomic research.

Main Methods:

• The All of Us Biomedical Researcher (BR) Scholars Program provides a year-long training.
• An in-person computational boot camp introduces foundational skills using a cloud-based environment.
• Genomics tutorials focus on genome-wide association studies (GWASs) using Jupyter Notebooks and the Hail framework.

Main Results:

• Scholars gain hands-on experience in data preparation, quality control, and association testing.
• Participants successfully conduct a genome-wide association study (GWAS) and visualize findings.
• Researchers build confidence in computational resource management for large-scale data analysis.

Conclusions:

• The program successfully lowers barriers to entry for genomic research.
• It equips researchers from diverse backgrounds with essential computational genomics skills.
• This initiative promotes the study of representative populations, advancing precision medicine and equity.