SAIGEgds: Scalable Implementation of Generalized mixed models using GDS files in PheWAS

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

AuthorXiuwen 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
MaintainerXiuwen Zheng <[email protected]>
LicenseGPL-3
Version1.0.0
URL https://github.com/AbbVie-ComputationalGenomics/SAIGEgds
Package repositoryView on Bioconductor
Installation Install the latest version of this package by entering the following in R:
source("https://bioconductor.org/biocLite.R")
biocLite("SAIGEgds")

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SAIGEgds documentation built on Oct. 31, 2019, 3:09 a.m.