SAIGEgds

DOI: 10.18129/B9.bioc.SAIGEgds    

This is the development version of SAIGEgds; for the stable release version, see SAIGEgds.

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

Bioconductor version: Development (3.17)

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 for single variant tests, Zhou et al. 2018). 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.

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 (from within R, enter citation("SAIGEgds")):

Installation

To install this package, start R (version "4.3") and enter:

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("SAIGEgds")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

PDF   Reference Manual

Details

biocViews Genetics, GenomeWideAssociation, Software, StatisticalMethod
Version 1.13.0
In Bioconductor since BioC 3.10 (R-3.6) (3 years)
License GPL-3
Depends R (>= 3.5.0), gdsfmt(>= 1.20.0), SeqArray(>= 1.31.8), Rcpp
Imports methods, stats, utils, RcppParallel, SPAtest (>= 3.0.0)
LinkingTo Rcpp, RcppArmadillo, RcppParallel (>= 5.0.0)
Suggests parallel, crayon, RUnit, knitr, markdown, rmarkdown, BiocGenerics, SNPRelate, ggmanh
SystemRequirements C++11, GNU make
Enhances
URL https://github.com/AbbVie-ComputationalGenomics/SAIGEgds
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report  

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package
Windows Binary
macOS Binary (x86_64)
macOS Binary (arm64)
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/
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