GxEsum: a novel approach to estimate the phenotypic variance explained by genome-wide GxE interaction based on GWAS summary statistics for biobank-scale data.
GxEsum: a novel approach to estimate the phenotypic variance explained by genome-wide GxE interaction based on GWAS summary statistics for biobank-scale data.
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DOI：
10.1186/s13059-021-02403-1
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发表时间：
2021-06-21
期刊：
影响因子：
12.3
通讯作者：
Lee SH
中科院分区：
文献类型：
--
作者：
Shin J;Lee SH
响应于环境的遗传变异，即基因型与环境的相互作用（GxE），是复杂性状和疾病生物学的基础。然而，现有的方法计算量大，无法处理生物库规模的数据。在这里，我们介绍GxEsum，一种基于GWAS汇总统计量估计全基因组GxE解释的表型方差的方法。通过对288，837个个体的英国生物库的全面模拟和分析，我们表明GxEsum可以处理具有受控I型错误率和无偏GxE估计的大规模生物库数据集，其计算效率可以比现有的GxE方法高出数百倍。在线版本包含补充材料，可通过10.1186/s13059-021-02403-1获得。
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. The online version contains supplementary material available at 10.1186/s13059-021-02403-1.