title: EpiGPU: exhaustive pairwise epistasis scans parallelized on consumer level graphics cards.
abstract: BACKGROUND
  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.
  
  
  RESULTS
  By partitioning the 2D search grid across the multicore architecture of a modern consumer graphics processing unit (GPU), we report a 92× increase in the speed of an exhaustive pairwise epistasis scan for a quantitative phenotype, and we expect the speed to increase as graphics cards continue to improve. To achieve a comparable computational improvement without a graphics card would require a large compute-cluster, an option that is often financially non-viable. The implementation presented uses OpenCL--an open-source library designed to run on any commercially available GPU and on any operating system.
  
  
  BACKGROUND
  The software is free, open-source, platformindependent and GPU-vendor independent. It can be downloaded from http://sourceforge.net/projects/epigpu/.
authors.affiliation: Division of Genetics and Genomics, The Roslin Institute and R(D)SVS, University of Edinburgh, Easter Bush, Midlothian, EH25 9RG, UK. gib.hemani@roslin.ed.ac.uk
authors.forename: Gibran
authors.initials: G
authors.lastname: Hemani
authors.forename: Athanasios
authors.initials: A
authors.lastname: Theocharidis
authors.forename: Wenhua
authors.initials: W
authors.lastname: Wei
authors.forename: Chris
authors.initials: C
authors.lastname: Haley
mesh_terms: D003196:Computer Graphics; D004843:Epistasis, Genetic; D055106:Genome-Wide Association Study; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide; D012984:Software