GRAB.SAGELD

<p>SAGELD method is Scalable and Accurate algorithm for Gene-Environment
interaction analysis using Longitudinal Data for related samples in a
large-scale biobank. SAGELD extended SPA<sub>GRM</sub> to support
gene-environment interaction analysis.</p>

Provides a comprehensive suite of genome-wide association study (GWAS) methods
specifically designed for biobank-scale data, including but not limited to, robust approaches
for time-to-event traits (Li et al., 2025 <doi:10.1038/s43588-025-00864-z>) and ordinal
categorical traits (Bi et al., 2021 <doi:10.1016/j.ajhg.2021.03.019>). The package also offers
general frameworks for GWAS of any trait type (Bi et al., 2020 <doi:10.1016/j.ajhg.2020.06.003>),
while accounting for sample relatedness (Xu et al., 2025 <doi:10.1038/s41467-025-56669-1>) or
population structure (Ma et al., 2025 <doi:10.1186/s13059-025-03827-9>). By accurately
approximating score statistic distributions using saddlepoint approximation (SPA), these
methods can effectively control type I error rates for rare variants and in the presence of
unbalanced phenotype distributions. Additionally, the package includes functions for simulating
genotype and phenotype data to support research and method development.

GRAB.SAGELD: SAGELD method in GRAB package

Description

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