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DOI: 10.18129/B9.bioc.SNPRelate    

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

Parallel Computing Toolset for Relatedness and Principal Component Analysis of SNP Data

Bioconductor version: Development (3.6)

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 GDS format is also used by the GWASTools package with the support of S4 classes and generic functions. The extended GDS format is implemented in the SeqArray package to support the storage of single nucleotide variations (SNVs), insertion/deletion polymorphism (indel) and structural variation calls.

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

Maintainer: Xiuwen Zheng <zhengx at>

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biocViews Genetics, Infrastructure, PrincipalComponent, Software, StatisticalMethod
Version 1.11.2
In Bioconductor since BioC 3.0 (R-3.1) (3 years)
License GPL-3
Depends R (>= 2.15), gdsfmt(>= 1.8.3)
LinkingTo gdsfmt
Suggests parallel, RUnit, knitr, MASS, BiocGenerics
Enhances SeqArray(>= 1.12.0)
Depends On Me
Imports Me
Suggests Me GENESIS, GWASTools, HIBAG, SeqArray
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