Sample Size and Statistical Power Calculation in Genetic Association Studies
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Abstract
A sample size with sufficient statistical power is critical to the success of genetic association studies to detect causal genes of human complex diseases. Genome-wide association studies require much larger sample sizes to achieve an adequate statistical power. We estimated the statistical power with increasing numbers of markers analyzed and compared the sample sizes that were required in case-control studies and case-parent studies. We computed the effective sample size and statistical power using Genetic Power Calculator. An analysis using a larger number of markers requires a larger sample size. Testing a single-nucleotide polymorphism (SNP) marker requires 248 cases, while testing 500,000 SNPs and 1…
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Topics
Keywords
- Sample size determination
- Association (psychology)
- Sample (material)
- Statistical power
- Statistics
- Genetic association
- Power (physics)
- Econometrics
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