cpvSNP

cpvSNP combines SNP-level association p-values into gene set–level p-values to assess gene set associations using the GLOSSI and VEGAS methods within the Bioconductor/R environment.

Key Features:

• Gene Set Association P-Values: Calculates a single association p-value for each gene set by combining SNP-level p-values.
• GLOSSI (Gene Set Level Omnibus Statistical Test): Aggregates SNP p-values under the assumption of independent SNPs and does not account for linkage disequilibrium (LD).
• VEGAS (Variable Effects Gene Set Analysis): Accounts for correlation or LD among SNPs within a gene set using SNP correlation information.
• Input Requirements: Requires SNP p-values and gene sets, with an optional SNP correlation matrix to model LD for VEGAS.
• Implementation: Distributed within the Bioconductor project and implemented for use in R.

Scientific Applications:

• Gene set–level association testing: Identify gene sets associated with complex traits or diseases by aggregating SNP-level association signals.
• LD-aware gene set analysis: Evaluate gene sets in contexts where SNP correlation or linkage disequilibrium influences association signals using VEGAS.

Methodology:

Combines SNP-level p-values into gene-set p-values using statistical p-value combination approaches, implementing GLOSSI for independent SNPs and VEGAS to incorporate SNP correlation or LD via a supplied correlation matrix.