SAIGEgds

Scalable Implementation of Generalized mixed models using GDS files in Phenome-Wide Association Studies

Bioconductor version: 3.23 · Package version: 2.12.0

Scalable implementation of generalized mixed models with highly optimized C++ implementation and integration with Genomic Data Structure (GDS) files. It is designed for single variant tests and set-based aggregate tests in large-scale Phenome-wide Association Studies (PheWAS) with millions of variants and samples, controlling for sample structure and case-control imbalance. The implementation is based on the SAIGE R package (v0.45, Zhou et al. 2018 and Zhou et al. 2020), and it is extended to include the state-of-the-art ACAT-O set-based tests. Benchmarks show that SAIGEgds is significantly faster than the SAIGE R package. Optional OpenCL-based GPU acceleration is supported for the GRM cross-product computation in null model fitting and for GRM construction.

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("SAIGEgds")