EpiGPU: exhaustive pairwise epistasis scans parallelized on consumer level graphics cards
Author(s) -
Gibran Hemani,
Athanasios Theocharidis,
Wenhua Wei,
Chris Haley
Publication year - 2011
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btr172
Subject(s) - computer science , graphics , pairwise comparison , epistasis , software , cuda , graphics processing unit , multi core processor , parallel computing , data mining , operating system , artificial intelligence , biology , biochemistry , gene
Hundreds of genome-wide association studies have been performed over the last decade, but as single nucleotide polymorphism (SNP) chip density has increased so has the computational burden to search for epistasis [for n SNPs the computational time resource is O(n(n-1)/2)]. While the theoretical contribution of epistasis toward phenotypes of medical and economic importance is widely discussed, empirical evidence is conspicuously absent because its analysis is often computationally prohibitive. To facilitate resolution in this field, tools must be made available that can render the search for epistasis universally viable in terms of hardware availability, cost and computational time.
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