PGSXplorer

PGSXplorer automates quality control, phasing, imputation, and polygenic score model construction using reference GWAS data through an integrated Nextflow DSL2 pipeline.

Key Features:

• Quality Control: Performs comprehensive quality control of genomic data as an integrated pipeline step.
• Phasing and Imputation: Automates phasing and imputation of genomic data for PGS model development.
• Multi-Tool Integration: Integrates multiple PGS development tools including PLINK, PRSice-2, LD-Pred2, Lassosum2, MegaPRS, SBayesR-C, PRS-CSx, and MUSSEL.
• Multi-Population Analysis: Supports both single- and multi-population analyses through multi-origin data integration.
• Scalability: Demonstrates scalability for analyses across different population structures using synthetic datasets.

Scientific Applications:

• Polygenic Score Development: Constructs PGS models from reference GWAS data for complex disease genetic research.
• Cross-Population Generalizability: Improves PGS generalizability through integration of multi-origin genomic data.
• Precision Medicine Research: Advances individualized medicine by enabling standardized PGS development pipelines.

Methodology:

PGSXplorer is implemented as a Nextflow DSL2 pipeline with Docker encapsulation, automating phasing, imputation, and PGS model construction using reference GWAS data.