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Parallel computing toolset for relatedness and principal component analysis of SNP data

Bioconductor version: 3.0

Genome-wide association studies (GWAS) are widely used to investigate the genetic basis of diseases and traits, but they pose many computational challenges. We developed an R package SNPRelate to provide a binary format for single-nucleotide polymorphism (SNP) data in GWAS utilizing CoreArray Genomic Data Structure (GDS) data files. The GDS format offers the efficient operations specifically designed for integers with two bits, since a SNP could occupy only two bits. SNPRelate is also designed to accelerate two key computations on SNP data using parallel computing for multi-core symmetric multiprocessing computer architectures: Principal Component Analysis (PCA) and relatedness analysis using Identity-By-Descent measures. The SNP format in this package is also used by the GWASTools package with the support of S4 classes and generic functions.

Author: Xiuwen Zheng [aut, cre], Stephanie Gogarten [ctb], Cathy Laurie [ctb], Bruce Weir [ctb, ths]

Maintainer: Xiuwen Zheng <zhengx at>

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PDF R Script SNPRelate Tutorial
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Text   NEWS


biocViews Genetics, Infrastructure, PrincipalComponent, Software, StatisticalMethod
Version 1.0.1
In Bioconductor since BioC 3.0 (R-3.1)
License GPL-3
Depends R (>= 2.14), gdsfmt(>= 1.2.2)
LinkingTo gdsfmt
Suggests parallel, RUnit, lattice, BiocStyle, BiocGenerics, knitr
Depends On Me
Imports Me
Suggests Me GWASTools
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