GCPBayes pipeline

GCPBayes performs Bayesian cross-phenotype gene-level analysis to detect pleiotropic genes from GWAS summary statistics across multiple traits.

Key Features:

• Cross-Phenotype Gene-Set Analysis: Performs gene-set and gene-level analysis across different phenotypes to identify genes with pleiotropic effects.
• Bayesian Inference Framework: Implements a Bayesian framework for integrative analysis of multiple traits to estimate shared genetic influences.
• Scripted Pipeline: Integrates executable scripts in Bash and R to run the analytical workflow.
• Visualization Tools: Generates plots to visualize analysis outputs and support interpretation of results.
• Efficiency Recommendations: Provides parameter-selection guidance to optimize computational efficiency for genome-scale GWAS data.

Scientific Applications:

• GWAS Summary Statistics Analysis: Applied to publicly available GWAS summary statistics to perform gene-level cross-phenotype analyses.
• Cancer Susceptibility Studies: Used to identify and corroborate pleiotropic genes and novel genomic regions associated with breast cancer and ovarian cancer susceptibility.

Methodology:

Uses a Bayesian framework for cross-phenotype gene-set analysis to integrate GWAS summary statistics from multiple traits, automating the analytical process and producing visualizations to identify shared genetic influences.