Home | SAIGE SAIGE is an R package developed with Rcpp for genome-wide association tests in large-scale data sets and biobanks The method accounts for sample relatedness based on the generalized mixed models allows for model fitting with either full or sparse genetic relationship matrix (GRM) works for quantitative and binary traits
GWAS方法 – SAIGE 校正病例对照失衡的广义线性混合模型 SAIGE全称是 Scalable and Accurate Implementation of GEneralized mixed model 广义混合模型的可扩展且准确的实现。 SAIGE 与 bolt-lmm (GWASLab：基于高斯混合模型的关联检验 Bolt-LMM – GWAS方法) 或 regenie (GWASLab：高效的全基因组回归 Regenie - GWAS方法) 类似，都需要两个步骤。
GitHub - weizhouUMICH SAIGE SAIGE is an R package with Scalable and Accurate Implementation of Generalized mixed model (Chen, H et al 2016) It accounts for sample relatedness and is feasible for genetic association tests in large cohorts and biobanks (N > 400,000)
Development for SAIGE and SAIGE-GENE (+) - GitHub Please find the https: saigegit github io SAIGE-doc for documentation SAIGE is an R package developed with Rcpp for genome-wide association tests in large-scale data sets and biobanks
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