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SEAGLE  

Scalable Exact Algorithm for Large-Scale Set-Based Gene-Environment Interaction Tests
View on CRAN: Click here


Download and install SEAGLE package within the R console
Install from CRAN:
install.packages("SEAGLE")

Install from Github:
library("remotes")
install_github("cran/SEAGLE")

Install by package version:
library("remotes")
install_version("SEAGLE", "1.0.1")



Attach the package and use:
library("SEAGLE")
Maintained by
Jocelyn Chi
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-06-07
Latest Update: 2021-11-05
Description:
The explosion of biobank data offers immediate opportunities for gene-environment (GxE) interaction studies of complex diseases because of the large sample sizes and rich collection in genetic and non-genetic information. However, the extremely large sample size also introduces new computational challenges in GxE assessment, especially for set-based 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 Large-scale Set-based GxE tests, to permit GxE VC test scalable to biobank data. 'SEAGLE' employs modern matrix computations to achieve the same
How to cite:
Jocelyn Chi (2021). SEAGLE: Scalable Exact Algorithm for Large-Scale Set-Based Gene-Environment Interaction Tests. R package version 1.0.1, https://cran.r-project.org/web/packages/SEAGLE
Previous versions and publish date:
1.0.0 (2021-06-07 09:10)
Other packages that cited SEAGLE R package
View SEAGLE citation profile
Other R packages that SEAGLE depends, imports, suggests or enhances
Functions, R codes and Examples using the SEAGLE R package
Some associated functions: Rinv.AtG . Rinv.u . SEAGLE . Vinv . applyAt . cosihap . estimate.vc . makeSimData . prep.SEAGLE . 
Some associated R codes: data.R . em_reml.R . makeData.R . prepData.R . score.R .  Full SEAGLE package functions and examples
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