INRICH: interval-based enrichment analysis for genome-wide association studies

Area of Science:

• Genetics
• Bioinformatics
• Computational Biology

Background:

• Genome-wide association studies (GWAS) are crucial for identifying genetic variants associated with diseases.
• Existing gene-set enrichment methods often fail to account for genomic biases like varying gene size, SNP density, and linkage disequilibrium.
• Overlapping gene annotations can also confound enrichment analyses.

Purpose of the Study:

• To introduce INRICH (INterval enRICHment analysis), a novel pathway-based tool for GWAS.
• To provide a robust method for identifying enriched association signals across genomic intervals.
• To address limitations of existing methods by accounting for genomic biases and gene set overlaps.

Main Methods:

• INRICH employs a pathway-based approach to test for enriched association signals within predefined gene sets across independent genomic intervals.
• A genomic permutation procedure is utilized to generate experiment-wide empirical significance values.
• The method accounts for biases such as varying gene size, SNP density, linkage disequilibrium, and overlapping gene annotations.

Main Results:

• INRICH demonstrates wide applicability, fast running times, and robustness against common genomic biases.
• Simulations confirm a properly controlled type I error rate and reasonable statistical power across diverse parameter settings.
• Application of INRICH to the NHGRI GWAS catalog serves as a proof of principle for its utility.

Conclusions:

• INRICH offers a robust and efficient tool for pathway-based genome-wide association analysis.
• The method effectively addresses confounding factors often overlooked by other gene-set enrichment techniques.
• INRICH enhances the analysis of GWAS data by providing reliable identification of enriched association signals in gene sets.