The explosion of biobank data offers immediate opportunities for geneenvironment (GxE) interaction studies of complex diseases because of the large sample sizes and rich collection in genetic and nongenetic information. However, the extremely large sample size also introduces new computational challenges in GxE assessment, especially for setbased GxE variance component (VC) tests, a widely used strategy to boost overall GxE signals and to evaluate the joint GxE effect of multiple variants from a biologically meaningful unit (e.g., gene). We present 'SEAGLE', a Scalable Exact AlGorithm for Largescale Setbased GxE tests, to permit GxE VC test scalable to biobank data. 'SEAGLE' employs modern matrix computations to achieve the same “exact” results as the original GxE VC tests, and does not impose additional assumptions nor relies on approximations. 'SEAGLE' can easily accommodate sample sizes in the order of 10^5, is implementable on standard laptops, and does not require specialized equipment. The accompanying manuscript for this package can be found at Chi, Ipsen, Hsiao, Lin, Wang, Lee, Lu, and Tzeng. (2021+) <arXiv:2105.03228>.
Package details 


Author  Jocelyn Chi [aut, cre], Ilse Ipsen [aut], JungYing Tzeng [aut] 
Maintainer  Jocelyn Chi <jocetchi@gmail.com> 
License  GPL3 
Version  1.0.1 
URL  https://github.com/jocelynchi/SEAGLE 
Package repository  View on CRAN 
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