| Title: | Joint testing of rare variant burden scores using non-negative least squares |
| Journal: | American Journal of Human Genetics |
| Published: | 3 Oct 2024 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/39366334/ |
| DOI: | https://doi.org/10.1016/j.ajhg.2024.08.021 |
Publication 13288
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Abstract
Gene-based burden tests are a popular and powerful approach for analysis of exome-wide association studies. These approaches combine sets of variants within a gene into a single burden score that is then tested for association. Typically, a range of burden scores are calculated and tested across a range of annotation classes and frequency bins. Correlation between these tests can complicate the multiple testing correction and hamper interpretation of the results. We introduce a method called the sparse burden association test (SBAT) that tests the joint set of burden scores under the assumption that causal burden scores act in the same effect direction. The method simultaneously assesses the significance of the model fit and selects the set of burden scores that best explain the association at the same time. Using simulated data, we show that the method is well calibrated and highlight scenarios where the test outperforms existing gene-based tests. We apply the method to 73 quantitative traits from the UK Biobank, showing that SBAT is a valuable additional gene-based test when combined with other existing approaches. This test is implemented in the REGENIE software.</p>
8 Keywords
- Computer Simulation
- Exome
- Genetic Variation
- Genome-Wide Association Study
- Humans
- Least-Squares Analysis
- Models, Genetic
- Software
20 Authors
- Andrey Ziyatdinov
- Joelle Mbatchou
- Anthony Marcketta
- Joshua Backman
- Sheila Gaynor
- Yuxin Zou
- Tyler Joseph
- Benjamin Geraghty
- Joseph Herman
- Kyoko Watanabe
- Arkopravo Ghosh
- Jack Kosmicki
- Adam Locke
- Regeneron Genetics Center
- Timothy Thornton
- Hyun Min Kang
- Manuel Ferreira
- Aris Baras
- Goncalo Abecasis
- Jonathan Marchini
1 Application
| Application ID | Title |
|---|---|
| 26041 | Large-Scale Sequencing in the UK Biobank to Facilitate Gene Discovery, Genome Sciences, and Precision Medicine |
Enabling scientific discoveries that improve human health