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Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
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EraSOR: a software tool to eliminate inflation caused by sample overlap in polygenic score analyses
Shing Wan Choi1,2, Timothy Shin Heng Mak3, Clive J Hoggart1
1Department of Genetics and Genomic Sciences, Icahn School of Medicine, Mount Sinai, New York City, NY 10029, USA.
Gigascience
|June 16, 2023
Summary
Sample overlap significantly inflates polygenic risk score (PRS) results. A new method, EraSOR, effectively corrects for this inflation and relatedness, providing more reliable PRS analyses.
Area of Science:
- Genetics
- Biomedical Research
- Statistical Genomics
Background:
- Polygenic risk score (PRS) analyses are increasingly common in biomedical research.
- Growing study sizes increase the risk of sample overlap between genome-wide association study (GWAS) discovery and PRS target samples.
- The impact of sample overlap on PRS results has not been quantified, and analytical solutions are lacking.
Purpose of the Study:
- To investigate the scale of the sample overlap problem in PRS studies.
- To develop and introduce a method to correct for sample overlap and relatedness in PRS analyses.
Main Methods:
- Comprehensive investigation into the impact of sample overlap on PRS results.
- Development and application of the EraSOR (Erase Sample Overlap and Relatedness) method and software.
Main Results:
- PRS results are substantially inflated even with minimal sample overlap.
- EraSOR effectively eliminates inflation caused by sample overlap and close relatedness in most tested scenarios.
Conclusions:
- EraSOR is a valuable tool for PRS studies with target samples >1,000.
- It can mitigate effects of known/unknown overlap and relatedness or serve as a sensitivity analysis tool.
- EraSOR provides a lower bound for PRS results when accounting for potential sample overlap.
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