CRAN/E | SEAGLE

SEAGLE

Scalable Exact Algorithm for Large-Scale Set-Based Gene-Environment Interaction Tests

Installation

About

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 “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+) .

Citation SEAGLE citation info
github.com/jocelynchi/SEAGLE

Key Metrics

Version 1.0.1
R ≥ 3.5.0
Published 2021-11-05 951 days ago
Needs compilation? no
License GPL-3
CRAN checks SEAGLE results

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Maintainer

Maintainer

Jocelyn Chi

Authors

Jocelyn Chi

aut / cre

Ilse Ipsen

aut

Jung-Ying Tzeng

aut

Material

README
Reference manual
Package source

Vignettes

example1
example2
example3
example4

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

SEAGLE archive

Depends

R ≥ 3.5.0
Matrix
CompQuadForm

Suggests

rmarkdown
knitr