LD Select

LD Select identifies a maximally informative set of tagSNPs by analyzing linkage disequilibrium (LD) patterns among single-nucleotide polymorphisms (SNPs) to optimize SNP selection for genetic association studies.

Key Features:

• Linkage Disequilibrium Analysis: Evaluates LD between polymorphic sites using the r² statistic, a measure directly related to statistical power for detecting associations with unassayed genetic variants.
• TagSNP Selection Algorithm: Selects tagSNPs to represent all known common polymorphisms within a candidate gene locus so that each variant is either directly assayed or exhibits strong association (r² > 0.8) with a chosen tagSNP.
• Haplotype Resolution: At stringent r² thresholds, the selected tagSNPs can resolve over 80% of haplotypes across candidate genes and allow analysis of specific haplotypes and clades in nonrecombinant regions, maintained regardless of recombination events.
• Population-Specific Analysis: Recommends selecting tagSNPs separately for populations with distinct ancestries because common genetic variation can differ between populations.

Scientific Applications:

• Candidate-Gene Association Studies: Reduces the number of SNPs required for genotyping without losing significant information, improving efficiency and cost-effectiveness of studies to identify disease-associated variants.
• Comprehensive Genetic Variation Analysis: Facilitates thorough examination of common functional variations within candidate genes to aid understanding of their roles in heritable diseases.

Methodology:

Calculates LD between SNPs using the r² statistic and selects a maximally informative set of tagSNPs by applying a high r² threshold (e.g., >0.8) to ensure coverage of common polymorphisms and inference of unassayed variants.