RegionalP

RegionalP quantifies the over-representation of associated single nucleotide polymorphisms (SNPs) within predefined genomic regions to provide regional evidence of phenotypic associations in genome-wide association studies (GWAS).

Key Features:

• Integration of linkage disequilibrium (LD): Incorporates regional LD patterns to account for the genetic architecture underlying association signals.
• Multi-ethnic and multi-platform compatibility: Accommodates differing LD patterns and allelic heterogeneity across populations and supports data from diverse genotyping platforms.
• Support for dichotomous and quantitative traits: Applies to both binary (dichotomous) and quantitative phenotypes.
• Gene-based and pathway-based analysis extension: Extends regional SNP analysis to gene-level and pathway-level analyses to probe biological mechanisms.

Scientific Applications:

• Enhanced association evidence: In a study of type 2 diabetes (T2D) across three South-East Asian populations, RegionalP increased association evidence in regions previously implicated in T2D etiology.
• Discovery of novel associations: Identified two novel gene regions and a biologically plausible pathway associated with T2D that were validated using data from the Wellcome Trust Case Control Consortium (WTCCC).

Methodology:

RegionalP integrates regional linkage disequilibrium (LD) patterns to assess over-representation of associated SNPs within predefined genomic regions and combines evidence across multiple studies while accommodating different genotyping platforms and population-specific LD and allelic variation.