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")):
Huber W, Carey VJ, Gentleman R, Anders S, Carlson M, Carvalho BS, Bravo HC, Davis S, Gatto L, Girke T, Gottardo R, Hahne F, Hansen KD, Irizarry RA, Lawrence M, Love MI, MacDonald J, Obenchain V, Oleś AK, Pagès H, Reyes A, Shannon P, Smyth GK, Tenenbaum D, Waldron L, Morgan M (2015). "Orchestrating high-throughput genomic analysis with Bioconductor." Nature Methods, 12(2), 115–121. doi:10.1038/nmeth.3252.
Gentleman RC, Carey VJ, Bates DM, Bolstad B, Dettling M, Dudoit S, Ellis B, Gautier L, Ge Y, Gentry J, Hornik K, Hothorn T, Huber W, Iacus S, Irizarry R, Leisch F, Li C, Maechler M, Rossini AJ, Sawitzki G, Smith C, Smyth G, Tierney L, Yang JYH, Zhang J (2004). "Bioconductor: open software development for computational biology and bioinformatics." Genome Biology, 5(10), R80. doi:10.1186/gb-2004-5-10-r80.
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 |
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 |
| Bioc Package Browser | https://code.bioconductor.org/browse/SAIGEgds/ |
| Package Short Url | https://bioconductor.org/packages/SAIGEgds/ |
| Package Downloads Report | Download Stats |