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Updated: Aug 28, 2025
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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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Efficient permutation-based genome-wide association studies for normal and skewed phenotypic distributions
Maura John1,2, Markus J Ankenbrand3, Carolin Artmann3
1Technical University of Munich, Campus Straubing for Biotechnology and Sustainability, Bioinformatics, 94315 Straubing, Germany.
Bioinformatics (Oxford, England)
|September 20, 2022
Summary
We developed permGWAS, an efficient tool for genome-wide association studies (GWAS) that uses permutation-based thresholds to improve the accuracy of genetic association discovery. This method offers faster computation and lower false discovery rates for complex traits.
Area of Science:
- Genetics
- Bioinformatics
- Computational Biology
Background:
- Genome-wide association studies (GWAS) are crucial for understanding complex genotype-phenotype relationships.
- Linear mixed models (LMMs) are widely used in GWAS but often violate assumptions, leading to inaccurate results.
- Permutation-based methods offer more realistic significance thresholds but are computationally intensive.
Purpose of the Study:
- To introduce permGWAS, an efficient reformulation of LMMs for GWAS.
- To enable the use of computationally feasible permutation-based significance thresholds.
- To improve the accuracy and refine the interpretation of GWAS results.
Main Methods:
- Developed permGWAS, an LMM reformulation utilizing 4D tensors.
- Implemented permutation-based significance thresholding within the permGWAS framework.
- Evaluated permGWAS performance against state-of-the-art LMMs regarding runtime and accuracy.
Main Results:
- permGWAS significantly outperforms current LMMs in terms of runtime.
- Permutation-based thresholds provided lower false discovery rates for skewed phenotypes compared to Bonferroni correction.
- Successfully re-analyzed over 500 Arabidopsis thaliana phenotypes in under 8 days on a single GPU.
Conclusions:
- permGWAS offers an efficient and accurate approach to GWAS.
- The use of permutation-based thresholds enhances the reliability of GWAS findings.
- permGWAS facilitates improved interpretation of genetic associations for complex traits.
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