SAIGE-BRUSH

SAIGE-BRUSH implements a cloud-based workflow that extends SAIGE to perform genome-wide association studies (GWAS) and related association analysis filtering and plot generation on large biobank datasets.

Key Features:

• Integration with SAIGE: Extends the SAIGE software for GWAS and association testing in large cohorts.
• Parallelization and data handling: Leverages parallel processing to manage and analyze large biobank datasets efficiently.
• Concurrency: Supports concurrent execution of tasks to increase throughput for large-scale analyses.
• Reproducibility: Incorporates features to enable reproducible GWAS workflows.
• Reusability: Enables reuse of SAIGE workflows and components across analyses.
• Scalability: Designed to scale to biobank-scale datasets and high-throughput analyses.
• Association analysis results filtering: Provides filtering of association analysis results.
• Output plot generation: Generates plots for visualization of association results.
• Cloud-based deployment (Google Cloud, CCPM): Implemented for cloud execution and currently deployed on Google Cloud by the Colorado Center for Personalized Medicine (CCPM).
• Support for multiple computational architectures: Adaptable to different computing environments and architectures.

Scientific Applications:

• Biobank-scale GWAS: Conduct genome-wide association studies on large biobank datasets.
• Genetic variant discovery: Identify genetic variants associated with traits or diseases.
• Scalable reproducible analyses: Enable reproducible and scalable association analyses across computational environments.

Methodology:

Builds on SAIGE and integrates parallel processing, concurrency, association analysis results filtering, output plot generation, and cloud-based deployment (including Google Cloud) to streamline GWAS workflows.