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Updated: Feb 12, 2026
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Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
Published on: July 27, 2021
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A simulation study investigating power estimates in phenome-wide association studies.
Anurag Verma1,2, Yuki Bradford1, Scott Dudek1
1Department of Genetics and Institute for Biomedical Informatics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA.
BMC Bioinformatics
|April 6, 2018
Summary
Phenome-wide association studies (PheWAS) require sufficient sample sizes for statistical power. For binary traits, over 200 cases are recommended, while quantitative traits need at least 1000 individuals for robust genetic variant association detection.
Area of Science:
- Genetics and Genomics
- Statistical Genetics
- Bioinformatics
Background:
- Phenome-wide association studies (PheWAS) link genetic variants to numerous health outcomes.
- Statistical power in PheWAS is influenced by sample size, trait type (binary/quantitative), and allele frequency.
- Optimizing PheWAS design requires understanding factors affecting statistical power.
Purpose of the Study:
- To investigate parameters influencing statistical power estimation in PheWAS.
- To provide data-driven guidelines for designing future PheWAS.
Main Methods:
- Conducted a simulation study of PheWAS.
- Varied parameters including sample size, case-control ratio, minor allele frequency, and disease penetrance.
- Simulated both binary and quantitative phenotypic measures.
Main Results:
- For binary traits, the number of cases significantly impacts statistical power more than the case-control ratio.
- A minimum of 200 cases is suggested for adequate power with common variants in binary trait PheWAS.
- For quantitative traits, sample sizes of 1000 or more individuals demonstrated optimal power.
Conclusions:
- Simulation analyses offer insights into statistical power for various PheWAS scenarios.
- Results can guide the design of future PheWAS to enhance association detection capabilities.
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