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). SAIGE performs single-variant association tests for binary traits and quantitative taits. For binary traits, SAIGE uses the saddlepoint approximation (SPA)(mhof, J. P. , 1961; Kuonen, D. 1999; Dey, R. 2017) to account for case-control imbalance. SAIGE-GENE (implemented in the SAIGE R package) performs gene- or region-based association tests (Burde, SKAT, SKAT-O) for binary traits and quantitative traits. Note: SAIGE-GENE accounts for case-control imbalance in gene-based tests (>=

More Information

For more information visit the SAIGE website.

Available Versions

These versions of SAIGE are available on the BEAR systems (BlueBEAR, BEARCloud VMs, and CaStLeS VMs). These will be retained in accordance with our Applications Support and Retention Policy.

Version BEAR Apps Version 2019a