SAIGEgds
This is the released version of SAIGEgds; for the devel version, see SAIGEgds.
Scalable Implementation of Generalized mixed models using GDS files in Phenome-Wide Association Studies
Bioconductor version: Release (3.23)
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.
Author: Xiuwen Zheng [aut, cre] 
, Wei Zhou [ctb] (the original author of the SAIGE R package), J. Wade Davis [ctb]
Maintainer: Xiuwen Zheng <xiuwen.zheng at abbvie.com>
citation("SAIGEgds")):Xiuwen Zheng. SAIGEgds: Scalable Implementation of Generalized mixed models using GDS files in Phenome-Wide Association Studies. doi:10.18129/B9.bioc.SAIGEgds, R package version 2.12.0, https://bioconductor.org/packages/SAIGEgds.
Generated from the package metadata; it may differ from the package's own citation.
Installation
To install this package, start R (version "4.6") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("SAIGEgds")For older versions of R, please refer to the appropriate Bioconductor release.
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("SAIGEgds")| SAIGEgds Tutorial (single variant tests) | HTML | R Script |
| Reference Manual | ||
| NEWS | Text |
Details
| biocViews | Genetics, GenomeWideAssociation, Software, StatisticalMethod |
| Version | 2.12.0 |
| In Bioconductor since | BioC 3.10 (R-3.6) (7 years) |
| License | GPL-3 |
| Depends | R (>= 4.0.0), gdsfmt (>= 1.28.0), SeqArray (>= 1.50.2), Rcpp |
| Imports | methods, stats, utils, Matrix, RcppParallel, SKAT, CompQuadForm, survey |
| System Requirements | GNU make |
| URL | https://github.com/AbbVie-ComputationalGenomics/SAIGEgds |
See More
| Suggests | parallel, markdown, rmarkdown, crayon, SNPRelate, RUnit, knitr, ggmanh, BiocGenerics |
| Linking To | Rcpp, RcppArmadillo, RcppParallel (>= 5.0.0) |
| Enhances | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Links To Me | |
| Build Report | Build Report, r-universe |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | SAIGEgds_2.12.0.tar.gz |
| Windows Binary (x86_64) | SAIGEgds_2.12.0.zip |
| macOS Binary (big-sur-x86_64) | SAIGEgds_2.12.0.tgz |
| macOS Binary (sonoma-arm64) | SAIGEgds_2.12.0.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/SAIGEgds |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/SAIGEgds |
| Package Short Url | https://bioconductor.org/packages/SAIGEgds/ |
| Package Downloads Report | Download Stats |