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 details |
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Author | Xiuwen Zheng [aut, cre] (<https://orcid.org/0000-0002-1390-0708>), Wei Zhou [ctb] (the original author of the SAIGE R package), J. Wade Davis [ctb] |
Bioconductor views | Genetics Software StatisticalMethod |
Maintainer | Xiuwen Zheng <xiuwen.zheng@abbvie.com> |
License | GPL-3 |
Version | 1.4.0 |
URL | https://github.com/AbbVie-ComputationalGenomics/SAIGEgds |
Package repository | View on Bioconductor |
Installation |
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