Global adaptive rank truncated product method for gene-set analysis in association studies

Area of Science:

• Genetics
• Bioinformatics
• Statistical Genetics

Background:

• Gene set analysis (GSA) evaluates the collective impact of genetic variants within genes or pathways on phenotypes.
• Individual variant analysis may miss subtle, cumulative effects.
• Existing methods like the Adaptive Rank Truncated Product (ARTP) have limitations in handling varied inheritance patterns.

Purpose of the Study:

• To introduce globalARTP, an enhanced implementation of the ARTP method for gene set analysis.
• To improve GSA by allowing single nucleotide polymorphisms (SNPs) within a set to have different modes of inheritance.
• To demonstrate the utility of globalARTP in genetic association studies, including complex diseases.

Main Methods:

• Development of globalARTP, a novel R function within the globalGSA package.
• Simulation studies to assess the statistical power of globalARTP across various scenarios.
• Application of globalARTP to an Alzheimer's disease case-control study focusing on the endocytosis pathway.

Main Results:

• globalARTP successfully accommodates multiple inheritance modes for SNPs within a gene or pathway.
• Simulation results demonstrate the power of the proposed methodology under different conditions.
• The gene set approach using globalARTP revealed insights into the endocytosis pathway in Alzheimer's disease.

Conclusions:

• globalARTP offers a more flexible and powerful approach to gene set analysis.
• The method effectively detects associations missed by individual SNP analyses.
• This tool facilitates deeper understanding of genetic contributions to complex phenotypes like Alzheimer's disease.