Login / Signup

GxEsum: a novel approach to estimate the phenotypic variance explained by genome-wide GxE interaction based on GWAS summary statistics for biobank-scale data.

Jisu ShinSang Hong Lee
Published in: Genome biology (2021)
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.
Keyphrases
  • genome wide
  • dna methylation
  • electronic health record
  • copy number
  • gene expression
  • molecular dynamics
  • cross sectional
  • data analysis
  • machine learning
  • genome wide association study
  • monte carlo