JEPEG

JEPEG aggregates eQTL and functional single nucleotide polymorphism (SNP) summary statistics from genome-wide association studies (GWAS) to test joint gene-level effects on phenotypes.

Key Features:

• Imputation of Summary Statistics: Uses GWAS summary statistics and correlation structures estimated from reference populations to impute summary statistics at unmeasured eQTLs.
• Joint Effect Testing: Tests the joint effect of measured and imputed eQTLs on gene expression or gene-associated phenotypes.
• Cosmopolitan Cohort Analysis (JEPEGMIX): JEPEGMIX extension estimates linkage disequilibrium (LD) patterns for mixed-ethnicity cohorts to enable imputation and joint testing in diverse populations.
• Computational Efficiency: Leverages LD patterns from reference panels to aggregate weak signals at the gene level while maintaining computational efficiency.

Scientific Applications:

• Multi-ethnic GWAS meta-analysis: Applied to GWAS meta-analysis summary statistics from multi-ethnic cohorts to detect gene-level associations.
• Analysis of complex traits across ancestries: Enables testing of gene-associated effects in cosmopolitan cohorts with mixed ethnicities.
• Schizophrenia genetics: Used on Psychiatric Genomics Consortium Schizophrenia stage 2 summary statistics to investigate genetic contributors, including immune system signals.

Methodology:

Integrates GWAS summary statistics with LD patterns derived from reference panels, imputes summary statistics at unmeasured eQTLs using estimated correlation structures, tests joint effects of measured and imputed eQTLs on gene-associated phenotypes, and JEPEGMIX estimates LD for mixed-ethnicity cohorts.