aSPU

aSPU implements adaptive sum of powered score tests for gene- and pathway-level association analysis using GWAS summary statistics.

Key Features:

• Adaptivity: Performs adaptive tests that accommodate diverse association patterns and operates on GWAS summary statistics without requiring individual-level genotype or phenotype data.
• Methodological extension: Extends two adaptive test methodologies originally developed for gene- and pathway-level associations with univariate traits to be applicable to GWAS summary statistics.
• Implementation: Provided as an R package for statistical computation and integration into analysis workflows.

Scientific Applications:

• Gene- and Pathway-Based Analyses: Enables testing of gene- and pathway-level associations to investigate the genetic architecture of complex traits beyond single-SNP analyses.
• Meta-Analyses: Applicable to meta-analytic studies by combining summary statistics from multiple GWAS.
• Validation and Example Traits: Validated using Wellcome Trust Case Control Consortium (WTCCC) GWAS data and applied to meta-analyzed datasets to identify genes and pathways associated with complex traits such as blood pressure.
• Resource Efficiency: Operates on summary statistics, reducing the need for sharing individual-level genotype or phenotype data.

Methodology:

Adaptive sum of powered score tests implemented via extensions of two adaptive test methodologies for gene- and pathway-level association with univariate traits applied to GWAS summary statistics.