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It is expected that a major part of the genetic risk for common human disorders is given by the interactions of multiple genes and environmental factors (1).
One of the most useful computational tools that are available for the detection of epistasis is the multifactor-dimensionality reduction (MDR) program (2,3). It is a freely available program (written in Java) that can identify significant interactions between genetic markers in case-control studies. It has a user friendly interface and can analyze datasets of typical sizes in short times in a normal PC. The initial paper describing MDR (2) has been cited more than 450 times and MDR has been used for the analysis of a broad range of human diseases and phenotypes. The use of this and other similar programs for the analysis of genetic association studies (including data from GWAS) will be useful for the identification of additional genes and pathways underlying the risk for common medical disorders (1,4). Contact: Professor Jason H. Moore, PhD, Computational Genetics Laboratory, Dartmouth Medical School, USA Email: jason.h.moore@dartmouth.edu "The current goal for MDR is to provide the computational algorithms necessary to scale the analysis to genome-wide association study data and eventually whole-genome sequence data. There is an emphasis on using biological knowledge to help guide an MDR search through an effectively infinite search space. A community of developers has formed to extend MDR in other important ways." Professor Jason H. Moore, PhD Links -Website of MDR -Website of the Computational Genetics Laboratory -Epistasis Blog -List of the 100 Publications Every Graduate Student Should Read (organized by Dr. Moore) References (1). Cordell HJ. Genome-wide association studies: Detecting gene-gene interactions that underlie human diseases. Nat Rev Genet. 2009 Jun; 10(6):392-404. (2) Ritchie MD, Hahn LW, Roodi N, Bailey LR, Dupont WD, Parl FF, Moore JH. Multifactor-dimensionality reduction reveals high-order interactions among estrogen-metabolism genes in sporadic breast cancer. Am J Hum Genet. 2001 Jul;69(1):138-47. (3) Hahn LW, Ritchie MD, Moore JH. Multifactor dimensionality reduction software for detecting gene-gene and gene-environment interactions. Bioinformatics. 2003 Feb 12;19(3):376-82. (4) Pattin KA, Moore JH. Exploiting the proteome to improve the genome-wide genetic analysis of epistasis in common human diseases. Hum Genet. 2008 Aug;124(1):19-29. Diego A. Forero, MD Editor, hum-molgen.org
Message posted by: Diego Forero
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