CCAFE: Estimating case and control allele frequencies from GWAS summary statistics

Area of Science:

• Genetics
• Bioinformatics
• Statistical Genetics

Background:

• Genetic summary statistics are valuable for understanding trait architecture but often lack complete data.
• Case and control allele frequencies (AFs) are crucial for many post-GWAS analyses but are not always published.

Purpose of the Study:

• To present methods and software for deriving case and control AFs from GWAS summary statistics.
• To improve the reusability of publicly available genetic data.

Main Methods:

• Developed methods to calculate case and control AFs using odds ratios, sample sizes, and either total AF or standard error (SE).
• Implemented a bias adjustment using gnomAD AFs when SE is used, as SE can underestimate AFs with covariates.
• Created the R package CCAFE (Case-Control Allele Frequency Estimation).

Main Results:

• Derivations using total AF were highly accurate in simulations and real data.
• Derivations using SE underestimated AFs when covariates were included in GWAS.
• Bias adjustment using gnomAD AFs improved accuracy when using SE.

Conclusions:

• The developed methods and CCAFE package enhance the utility of GWAS summary statistics.
• These tools promote data reusability in genetic research.
• Accurate allele frequency estimation is critical for advancing genetic studies.