| Title: | GxEsum: a novel approach to estimate the phenotypic variance explained by genome-wide GxE interaction based on GWAS summary statistics for biobank-scale data |
| Journal: | Genome Biology |
| Published: | 21 Jun 2021 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/34154633/ |
| DOI: | https://doi.org/10.1186/s13059-021-02403-1 |
| URL: | https://genomebiology.biomedcentral.com/counter/pdf/10.1186/s13059-021-02403-1 |
| Citations: | 22 (16 in last 2 years) as of 8 Aug 2024 |
Publication 5106
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Abstract
Genetic variation in response to the environment, that is, genotype-by-environment interaction (GxE), is fundamental in the biology of complex traits and diseases. However, existing methods are computationally demanding and infeasible to handle biobank-scale data. Here, we introduce GxEsum, a method for estimating the phenotypic variance explained by genome-wide GxE based on GWAS summary statistics. Through comprehensive simulations and analysis of UK Biobank with 288,837 individuals, we show that GxEsum can handle a large-scale biobank dataset with controlled type I error rates and unbiased GxE estimates, and its computational efficiency can be hundreds of times higher than existing GxE methods.14 Keywords
- Algorithms
- Biological Specimen Banks
- Body Mass Index
- Diabetes Mellitus, Type 2
- Gene-Environment Interaction
- Genetic Variation
- Genome, Human
- Genome-Wide Association Study
- Genotype
- Humans
- Hypertension
- Models, Genetic
- Multifactorial Inheritance
- Quantitative Trait, Heritable
2 Authors
- Jisu Shin
- Sang Hong Lee
Enabling scientific discoveries that improve human health