GAUSS

GAUSS analyzes summary statistics from large-scale genome-wide association studies using a multi-ethnic reference panel for ancestry-informed imputation and linkage disequilibrium calculation.

Key Features:

• Ancestry Proportion Estimation: GAUSS estimates the ancestry proportion of study cohorts.
• Ancestry-Informed Linkage Disequilibrium Calculation: GAUSS calculates ancestry-informed linkage disequilibrium for variants.
• Summary Statistics Imputation: GAUSS imputes summary statistics of unobserved variants, including rarer variants, using a multi-ethnic reference panel of 32 953 genomes from 29 ethnic groups.
• Transcriptome-Wide Association Studies: GAUSS conducts transcriptome-wide association studies (TWAS).
• Winner's Curse Correction: GAUSS corrects for Winner's Curse biases.

Scientific Applications:

• GWAS Re-analysis and Downstream Analysis: GAUSS facilitates re-analysis and downstream analysis of existing GWAS summary statistics without requiring individual-level genotype and phenotype data.
• Fine-mapping Support: GAUSS supports ancestry-informed imputation for downstream analyses such as fine-mapping.
• Cosmopolitan Cohort Analysis: GAUSS enables analysis of ethnically diverse cohorts through its multi-ethnic reference panel.

Methodology:

GAUSS implements summary-statistics-based methods in R, utilizing a multi-ethnic reference panel of 32 953 genomes from 29 ethnic groups for ancestry-informed imputation and linkage disequilibrium estimation.