recipe bioconductor-saigegds

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






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 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 original SAIGE R package (v0.29.4.4). SAIGEgds also implements some of the SPAtest functions in C to speed up the calculation of Saddlepoint approximation. Benchmarks show that SAIGEgds is 5 to 6 times faster than the original SAIGE R package.

package bioconductor-saigegds

(downloads) docker_bioconductor-saigegds


1.2.0-0, 1.0.0-0

Required By


With an activated Bioconda channel (see 2. Set up channels), install with:

conda install bioconductor-saigegds

and update with:

conda update bioconductor-saigegds

or use the docker container:

docker pull<tag>

(see bioconductor-saigegds/tags for valid values for <tag>)