SECA

SECA performs SNP effect concordance analysis using genome-wide association (GWA) summary results to assess pleiotropy and genetic overlap across phenotypes without requiring individual-level genotype data.

Key Features:

• GWA summary data input: Operates on summary-level GWA results including SNP effect sizes and p-values rather than individual-level genotype data.
• SNP effect concordance assessment: Assesses concordance of SNP effects across datasets by evaluating consistent effect directions and magnitudes.
• Pleiotropy and genetic overlap detection: Identifies SNPs and loci that exhibit pleiotropic effects and quantifies genetic overlap between traits.
• Validation with public summary data: Methodology has been validated using publicly available summary data from the Psychiatric Genomics Consortium.

Scientific Applications:

• Psychiatric genetics: Assess shared genetic factors and pleiotropy across psychiatric disorders using GWA summary results.
• Genetic architecture of complex traits: Identify and characterize genetic overlap and pleiotropic loci across diverse phenotypes.

Methodology:

Analyzes GWA summary results (effect sizes and p-values) to assess concordance of SNP effects across phenotypic datasets and identify SNPs with consistent effect directions or magnitudes.