Efficient two-stage genome-wide association designs based on false positive report probabilities

Area of Science:

• Genetics
• Genomics
• Statistical genetics

Background:

• Very-high-throughput (VHT) genotyping is expensive for large-scale genetic association studies.
• Identifying variants with modest effects on disease risk requires substantial sample sizes.

Purpose of the Study:

• To present a cost-effective two-stage genotyping strategy for genetic association studies.
• To maximize the detection of true disease-associated variants while controlling false positives.
• To offer a more powerful alternative to single-stage VHT genotyping within a fixed budget.

Main Methods:

• A two-stage genotyping approach: VHT genotyping on a subset of samples, followed by replication of promising variants.
• Statistical methods to optimize sample sizes and significance levels for each stage.
• Focus on limiting False Positive Report Probability (FPRP) to control false discoveries.

Main Results:

• The two-stage strategy demonstrates greater statistical power (more Expected True Positives) compared to single-stage VHT genotyping for a fixed budget.
• This approach offers significant cost savings by avoiding widespread VHT genotyping.
• Controlling FPRP is more resource-efficient than controlling family-wise error rates.

Conclusions:

• The proposed two-stage genotyping strategy is a powerful and economical method for large-scale genetic association studies.
• It effectively balances the detection of true genetic associations with the control of false positives.
• The method allows incorporation of prior biological knowledge, further refining the discovery process.