Division of Genetics and Genomics, The Roslin Institute and R(D)SVS, University of Edinburgh, Easter Bush, Midlothian, EH25 9RG, UK.
Bioinformatics. 2011 Jun 1;27(11):1462-5. doi: 10.1093/bioinformatics/btr172. Epub 2011 Apr 6.
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.
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.
The software is free, open-source, platformindependent and GPU-vendor independent. It can be downloaded from http://sourceforge.net/projects/epigpu/.
在过去的十年中，已经进行了数百项全基因组关联研究，但随着单核苷酸多态性（SNP）芯片密度的增加，搜索上位性的计算负担也增加了[对于 n 个 SNP，计算时间资源是 O(n(n-1)/2)]。虽然上位性对医学和经济重要性的表型的理论贡献被广泛讨论，但实证证据却明显缺失，因为其分析通常在计算上是不可行的。为了在这一领域取得进展，必须提供工具，使搜索上位性在硬件可用性、成本和计算时间方面普遍可行。
通过将 2D 搜索网格划分为现代消费者图形处理单元（GPU）的多核架构，我们报告了对定量表型进行全面成对上位性扫描的速度提高了 92 倍，并且我们预计随着图形卡的不断改进，速度会进一步提高。如果不使用图形卡来实现可比的计算改进，则需要一个大型计算集群，这在经济上往往是不可行的。所提出的实现使用 OpenCL——这是一个开源库，旨在在任何商业上可用的 GPU 和任何操作系统上运行。
该软件是免费的、开源的、与平台无关的，并且与 GPU 供应商无关。它可以从 http://sourceforge.net/projects/epigpu/ 下载。
