SNPALYZE

SNPALYZE performs AIC-based linkage disequilibrium estimation and genotyping data analysis to support case-control studies and fine gene mapping.

Key Features:

• Data Import Capability: Supports import of multiple genotyping data file formats for integration of genetic datasets.
• Case-Control Study Analysis: Handles case-control datasets by requiring and using additional columns that distinguish cases and controls.
• Linkage Disequilibrium (LD) Estimation: Estimates LD by comparing an independent model (IM; linkage equilibrium) with a dependent model (DM; linkage disequilibrium) using Akaike's Information Criterion (AIC).
• Comparison with Standard Measures: Enables comparison of AIC-derived LD estimates with standard measures D' and r².
• Fine Gene Mapping Application: Applies AIC-based LD estimates to inform fine gene mapping and identification of disease-associated loci in complex disease studies.

Scientific Applications:

• Case-Control Genetic Association: Analysis of genotyping data in case-control studies to assess associations between SNPs and phenotypes.
• Linkage Disequilibrium Assessment: Quantification of LD between single-nucleotide polymorphisms (SNPs) using AIC alongside D' and r².
• Fine Gene Mapping: Refinement of candidate loci in complex disease studies by using AIC-based LD information.
• Method Comparison: Evaluation of concordance and differences between AIC-based LD estimates and standard LD metrics D' and r².

Methodology:

Computes AIC(LD) as AIC(IM) - AIC(DM) by comparing independent and dependent models using Akaike's Information Criterion; positive AIC(LD) indicates linkage disequilibrium, negative indicates linkage equilibrium, and D' values below 0.2 are considered indicative of linkage equilibrium.