A high-performance computing toolset for relatedness and principal component analysis of SNP data

Genome-wide association studies are widely used to investigate the genetic basis of diseases and traits, but they pose many computational challenges. We developed gdsfmt and SNPRelate (R packages for multi-core symmetric multiprocessing computer architectures) to accelerate two key computations on S...

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Vydané v:	Bioinformatics Ročník 28; číslo 24; s. 3326 - 3328
Hlavní autori:	Zheng, Xiuwen, Levine, David, Shen, Jess, Gogarten, Stephanie M., Laurie, Cathy, Weir, Bruce S.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Oxford Oxford University Press 01.12.2012
Predmet:	Algorithms Applications Note Biological and medical sciences Fundamental and applied biological sciences. Psychology General aspects Genome-Wide Association Study Humans Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects) Polymorphism, Single Nucleotide Principal Component Analysis Software High performance Supercomputing Data analysis Data Single nucleotide polymorphism Computing Component Performance Principal component analysis
ISSN:	1367-4803, 1367-4811, 1367-4811, 1460-2059
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