Determinant-based grouping of SNPs and its application for detecting disease-associated genomic loci.

ABSTRACT: Groups of single nucleotide polymorphisms (SNPs) are more effective than individual SNPs in identifying genetic loci associated with diseases. However, an optimal method for grouping SNPs remains an open question. Here, we introduce a novel approach for SNP grouping, leveraging the determinant of linkage disequilibrium (LD) matrices as a comprehensive metric of multicollinearity. This method builds on the established use of determinants in regression analysis as an aggregate measure of variable interdependence. We proposed that SNPs be grouped by evaluating the determinant of their LD matrices, with the approach validated using both synthetic genotype-phenotype data and real-world data from genome-wide association studies (GWAS) of ischemic stroke. Application of this method identified two

SUBMITTER: Khvorykh G 

PROVIDER: S-EPMC11915498 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature