ASSET

ASSET performs subset-based analysis to identify genetic associations across heterogeneous traits and subtypes in genome-wide association studies (GWASs), accounting for variants that affect only subsets of traits and allowing concordant or discordant effect directions.

Key Features:

• Subset-Based Analysis: Exhaustively explores subsets of studies to identify association signals present in only a subset of traits or studies.
• Directional Flexibility: Detects associations with both concordant and discordant (opposite) effect directions among subsets.
• Efficient Approximation for P-Values: Incorporates an efficient approximation method to rapidly evaluate p-values.
• Improved Power and Interpretability: Enhances power to detect true associations and produces more interpretable results compared with traditional meta-analysis or pooled analysis.
• R Package Implementation: Implemented and distributed as an R package for analysis within the R environment.

Scientific Applications:

• Meta-Analysis of Case-Control Studies: Applied to meta-analyze separate case-control studies across six distinct cancer types to identify shared genetic factors.
• Pooled Analysis of Heterogeneous Subtypes: Applied to pooled analysis of glioma subtypes within brain tumors to address intra-study heterogeneity.
• Other Heterogeneous Data Analyses: Applicable to analyses of heterogeneous datasets where variants may have subset-specific or opposing effects.

Methodology:

Implemented as an R package that exhaustively explores study subsets, accommodates concordant and discordant effects across traits or subtypes, and uses an efficient approximation method to evaluate p-values.