Analysis of high-density single-nucleotide polymorphism data: three novel methods that control for linkage disequilibrium between markers in a linkage analysis

Abstract

We performed a multipoint linkage analysis for rheumatoid arthritis (RA) using high-density single-nucleotide polymorphism (SNP) data for chromosome 6 and chromosome 21 using Genetic Analysis Workshop 15 (GAW15) data. These regions were previously shown to have high LOD scores, not accounting for linkage disequilibrium (LD). We propose three novel methods to control for LD in a linkage analysis: allow for LD between markers using graphical modeling, eliminate high-LD markers by principal-component analysis (PCA) using haplotype data, and eliminate high-LD markers by PCA using genotype data. All three novel methods were compared to the previously published SNPLINK high-LD elimination method. Although all four methods verified the previous results, differences in linkage peak height and position were observed across methods. Additional work is required to further understand the effects of LD on linkage results and explore LD control methodology.