SNPTEST

SNPTEST performs statistical association testing of single nucleotide polymorphisms (SNPs) in genome-wide association studies to detect genetic effects on binary (case-control) and quantitative phenotypes using both Bayesian and Frequentist frameworks.

Key Features:

• Statistical Methods: Implements Bayesian and Frequentist association tests for binary (case-control) analyses and for single and multiple quantitative phenotypes.
• Covariate Conditioning: Conditions analyses on arbitrary sets of covariates or SNPs to control for confounding and secondary signals.
• Handling Imputed SNPs: Incorporates genotype imputation-aware analyses to test imputed SNPs and to support meta-analysis and fine-mapping.
• Performance Assessment: Assesses the performance of genotype imputation and association tests at imputed SNPs.

Scientific Applications:

• Genome-wide association studies (GWAS): Identify genetic factors involved in complex human diseases by testing SNP associations across the genome.
• Cross-phenotype validation: Validate and compare SNP associations across multiple disease phenotypes using shared control groups.
• Disease-specific replication: Identify and replicate association signals in diseases such as bipolar disorder, coronary artery disease, Crohn's disease, rheumatoid arthritis, type 1 diabetes, and type 2 diabetes.

Methodology:

Implements Bayesian and Frequentist statistical tests for binary and quantitative phenotypes, conditions on covariates or SNPs, integrates genotype imputation-aware testing, and evaluates imputation performance to support fine-mapping and meta-analysis.