Multifactor dimensionality reduction for graphics processing units enables genome-wide testing of epistasis in sporadic ALS
Department of Genetics, Dartmouth Medical School, Lebanon, NH 03756, USA
Bioinformatics (Oxford, England), Vol. 26, No. 5. (1 March 2010), pp. 694-695.
@article{greene2010multifactor,
title={Multifactor dimensionality reduction for graphics processing units enables genome-wide testing of epistasis in sporadic ALS},
author={Greene, C.S. and Sinnott-Armstrong, N.A. and Himmelstein, D.S. and Park, P.J. and Moore, J.H. and Harris, B.T.},
journal={Bioinformatics},
volume={26},
number={5},
pages={694},
issn={1367-4803},
year={2010},
publisher={Oxford Univ Press}
}
MOTIVATION: Epistasis, the presence of gene-gene interactions, has been hypothesized to be at the root of many common human diseases, but current genome-wide association studies largely ignore its role. Multifactor dimensionality reduction (MDR) is a powerful model-free method for detecting epistatic relationships between genes, but computational costs have made its application to genome-wide data difficult. Graphics processing units (GPUs), the hardware responsible for rendering computer games, are powerful parallel processors. Using GPUs to run MDR on a genome-wide dataset allows for statistically rigorous testing of epistasis. RESULTS: The implementation of MDR for GPUs (MDRGPU) includes core features of the widely used Java software package, MDR. This GPU implementation allows for large-scale analysis of epistasis at a dramatically lower cost than the standard CPU-based implementations. As a proof-of-concept, we applied this software to a genome-wide study of sporadic amyotrophic lateral sclerosis (ALS). We discovered a statistically significant two-SNP classifier and subsequently replicated the significance of these two SNPs in an independent study of ALS. MDRGPU makes the large-scale analysis of epistasis tractable and opens the door to statistically rigorous testing of interactions in genome-wide datasets. AVAILABILITY: MDRGPU is open source and available free of charge from http://www.sourceforge.net/projects/mdr.
November 7, 2010 by hgpu
