CLIN_SKAT: an R package to conduct association analysis using functionally relevant variants

Area of Science:

• Genetics
• Bioinformatics
• Statistical Genetics

Background:

• Next-generation sequencing data enables the study of low-frequency and rare variants beyond traditional genome-wide association studies (GWAS).
• Rare variants are crucial for explaining the heritability of complex diseases often missed by common variants.
• Current analysis strategies face bottlenecks due to the large volume of sequencing data.

Purpose of the Study:

• To introduce CLIN_SKAT, an R package designed for efficient analysis of genetic variants.
• To provide a user-friendly pipeline for extracting clinically relevant variants and performing gene-based association analysis.
• To improve the power of statistical association analysis for complex diseases.

Main Methods:

• CLIN_SKAT employs four functions for variant selection, gene mapping, population-specific weight calculation, and weighted case-control analysis.
• The package incorporates pre-analysis steps and customizable features to enhance the clinical relevance of SKAT (Sequence Kernel Association Test) results.
• It includes visualization tools for interpreting analysis outcomes.

Main Results:

• CLIN_SKAT facilitates the identification of clinically relevant variants and gene-level associations.
• The package offers customizable features and pre-analysis steps to refine association test results.
• Outputs are available in user-friendly tabular and graphical formats for publication.

Conclusions:

• CLIN_SKAT addresses the underpowering issue in statistical association analysis by focusing on biologically meaningful variants.
• The package reduces analytical complexity and computational resource requirements.
• It offers an integrated solution for identifying disease risk variants with improved statistical power and reduced dimensionality.