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Updated: Jul 3, 2025

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
Published on: July 27, 2021
Using Alternative Definitions of Controls to Increase Statistical Power in GWAS
This study introduces an ordinal model for genome-wide association studies (GWAS), enhancing statistical power by redefining case-control outcomes. This approach boosts power, comparable to a 10% sample size increase, for genetic discovery.
Area of Science:
- Genetics
- Biostatistics
- Computational Biology
Background:
- Genome-wide association studies (GWAS) often lack statistical power due to small effect sizes of single nucleotide polymorphisms (SNPs) and stringent multiple testing criteria.
- Increasing sample size is the conventional method to enhance GWAS power, but this can be resource-intensive.
Conclusions:
- Redefining outcomes into an ordinal variable is an effective strategy to enhance statistical power in GWAS.
- The proposed ordinal model offers a computationally efficient alternative to increasing sample size for genetic discovery.
- This approach has significant implications for identifying genetic associations with complex traits and diseases.
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