SNPinfo

SNPinfo facilitates selection and functional annotation of single nucleotide polymorphisms (SNPs) to prioritize variants for genetic association studies.

Key Features:

• Gene or linkage region specification: Enables specification of particular genes or linkage regions as the basis for SNP selection.
• Integration with GWAS results: Uses GWAS P-value data to identify SNPs in high linkage disequilibrium (LD) with significant GWAS SNPs.
• Tag SNP identification: Identifies tag SNPs for loci not in high LD with any GWAS SNPs to ensure comprehensive variant representation.
• Functional predictions: Predicts impacts of coding and non-coding SNPs on protein structure, gene regulation, splicing, and miRNA binding and assesses allele-specific effects.
• Customizable weights for functional categories: Permits assignment of different weights to functional categories to score and prioritize SNPs.
• Population-specific LD structure consideration: Accounts for LD structure across different populations to adapt GWAS findings between ethnic groups.

Scientific Applications:

• Genetic association studies: Prioritizes functionally relevant SNPs for follow-up in association analyses by integrating GWAS, LD, and functional data.
• Cross-population variant selection: Transfers GWAS signals across populations by selecting SNPs that reflect population-specific LD structure.
• Disease-specific panel design: Supports design of small SNP panels enriched for validated disease-associated variants, as demonstrated in prostate cancer studies.

Methodology:

Inputs genes or linkage regions and GWAS results (P-values); identifies SNPs in high LD with significant GWAS SNPs and selects tag SNPs where needed; applies algorithms to predict effects on protein structure, gene regulation, splicing, and miRNA binding; scores and prioritizes SNPs using customizable weights; and considers population-specific LD structure.