Corpus ID: 234094795

SEAGLE: A Scalable Exact Algorithm for Large-Scale Set-Based GxE Tests in Biobank Data

@inproceedings{Chi2021SEAGLEAS,
  title={SEAGLE: A Scalable Exact Algorithm for Large-Scale Set-Based GxE Tests in Biobank Data},
  author={Jocelyn T. Chi and Ilse C. F. Ipsen and T. Hsiao and Ching-Heng Lin and Li-San Wang and Wan-Ping Lee and T. Lu and J. Tzeng},
  year={2021}
}
The explosion of biobank data offers immediate opportunities for gene-environment (GxE) interaction studies of complex diseases because of the large sample sizes and the rich collection in genetic and non-genetic information. However, the extremely large sample size also introduces new computational challenges in G×E assessment, especially for set-based G×E variance component (VC) tests, which is a widely used strategy to boost overall G×E signals and to evaluate the joint G×E effect of… Expand

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