HTRX

HTRX identifies haplotypes composed of non-contiguous single nucleotide polymorphisms (SNPs) and quantifies the contributions of main effects and interactions to phenotypic variance in genome-wide association studies (GWAS).

Key Features:

• Non-Contiguous Haplotype Identification: Identifies haplotypes composed of non-contiguous SNPs that are associated with phenotypes.
• Interaction and Tagging Analysis: Quantifies both main effects and SNP–SNP interactions and captures tagging relationships among SNPs.
• Variance Attribution: Estimates the total variance attributable to main effects and interactions among non-contiguous SNPs.
• Cumulative HTRX Approach: Grows promising feature sets incrementally to reduce the search space and limit maximum feature-set complexity.
• Scalability: Computational time scales linearly with the number of SNPs, enabling analysis of large chromosome regions.
• Flexibility in Application: Applicable both before and after fine-mapping of GWAS hits.

Scientific Applications:

• GWAS signal dissection: Distinguishes potential causal signals from high linkage disequilibrium (LD) blocks within GWAS loci.
• Genetic architecture analysis: Dissects contributions of haplotypes and interactions to phenotypic variance in complex traits and diseases.

Methodology:

HTRX applies haplotype trend regression and related statistical models to capture relationships between non-contiguous SNPs and phenotypes, quantifies variance from main effects and interactions, and uses a Cumulative HTRX strategy that incrementally grows feature sets to reduce the search space.