pMDR
Method Description:
As a result of the International HapMap project and recent dramatic advances in genotyping, large scale whole genome case-control studies are now technologically feasible. Common, complex diseases, such as sporadic breast cancer and essential hypertension, are likely multifactorial in nature, and epistasis, or gene-gene interactions, may contribute to their etiology. Multifactor dimensionality reduction (MDR) has been previously introduced as a non-parametric, model free method for detecting gene-gene and gene-environment interactions. The original MDR software was designed for small candidate gene studies of less than 500 variables and is quickly overwhelmed by the large scale datasets being generated by current technologies. Parallel multifactor dimensionality reduction (pMDR) is a new implementation of the MDR algorithm that can scale to handle extremely large data sets, dramatically decreases single-processor runtimes, and can also use a parallel software framework to allow operation in a clustered computing environment to further reduce runtime.
The improved algorithm of pMDR allows for an unlimited number of variable states (for haplotype encoding) and an unlimited number of individuals. The number of variables and the order interaction to analyze (2 locus interactions, 3 locus interactions, etc) are limited only by machine memory and computation time. These improvements allow the analysis of higher order interactions for small datasets and make two-locus interactions computationally feasible for very large datasets.
Software Subscription
Relevant Publications:
- Bush WS, Dudek SM, Ritchie MD. Parallel Multifactor Dimensionality Reduction: a tool for the large scale analysis of gene-gene interactions. Bioinformatics, 22:2173-4 (2006).
- Hahn, L.W., Ritchie, M.D., and Moore, J.H. Multifactor dimensionality reduction software for detecting gene-gene and gene-environment interactions. Bioinformatics, 19, 376-382. (2003).
Related Links:
- International HapMap Project http://www.hapmap.org