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Two-stage designs for gene-disease association studies with sample size constraints
Jaya M Satagopan1, E S Venkatraman, Colin B Begg
1Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, NY 10021, USA. satagopj@mskcc.org
Biometrics
|September 2, 2004
Summary
This study introduces a cost-effective two-stage method for identifying disease-susceptibility markers. By evaluating markers in two stages, researchers can significantly reduce genotyping costs with minimal loss of statistical power.
Area of Science:
- Genetics
- Bioinformatics
- Statistical genomics
Background:
- Case-control studies identify genetic markers associated with disease risk.
- Genotyping numerous markers across all samples is resource-intensive.
Purpose of the Study:
- To propose and evaluate a cost-effective two-stage method for identifying disease-susceptibility markers.
- To reduce the total number of marker evaluations in genetic association studies.
Main Methods:
- A two-stage approach: Stage 1 evaluates all markers on a fraction of subjects; Stage 2 evaluates promising markers on remaining subjects.
- Simulations were used to assess the method's power and efficiency under various marker correlation scenarios.
Main Results:
- The two-stage method significantly reduces marker evaluations with minimal power loss, regardless of marker correlation.
- A specific guideline (50% subjects in Stage 1, top 10% markers in Stage 2) offers near-optimal power and a ~45% reduction in evaluations.
Conclusions:
- The proposed two-stage strategy is an efficient and powerful alternative for identifying disease-susceptibility markers.
- This method optimizes resource utilization in large-scale genetic association studies.
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