hgv_ldtools

hgv_ldtools analyzes linkage disequilibrium patterns among polymorphic sites within a genetic locus to select tagSNPs and assess haplotype structure for studying associations of common genetic polymorphisms with disease risk.

Key Features:

• TagSNP selection algorithm: selects a maximally informative set of common single-nucleotide polymorphisms (tagSNPs) based on linkage disequilibrium for efficient genotyping.
• LD metric (r^2): uses the r^2 linkage disequilibrium statistic, which correlates with statistical power to detect associations at unassayed sites.
• Coverage and haplotype resolution: resolves over 80% of haplotypes across candidate genes, including regions without recombination.
• r^2 thresholding: supports applying stringent r^2 thresholds (e.g., r^2 > 0.8) to capture allelic association patterns among common variants.
• Population-specific tagSNP selection: performs tagSNP selection tailored to population-specific patterns of common genetic variation.
• Haplotype and clade resolution: identifies haplotypes and clades of related haplotypes for detailed genetic mapping.

Scientific Applications:

• Candidate-gene association studies: facilitates selection and analysis of tagSNPs to interrogate common functional variation in candidate-gene association studies.
• Power optimization for association mapping: informs genotyping strategies by using r^2-based selection to maximize power to detect disease associations at unassayed sites.
• Haplotype mapping: supports resolving haplotypes and clades for detailed genetic mapping and interpretation of allelic architecture.

Methodology:

The software applies an algorithm that selects a maximally informative set of common SNPs using the r^2 linkage disequilibrium statistic, allows specification of r^2 thresholds (e.g., r^2 > 0.8), resolves over 80% of haplotypes across candidate genes including regions without recombination, and performs population-specific tagSNP selection.