1. On the use of multifactor dimensionality reduction (MDR) and classification and regression tree (CART) to identify haplotype-haplotype interactions in genetic studies
- Author
-
Ai-Ru Hsieh, Ching-Lin Hsiao, Hui-Min Wang, Cathy S.J. Fann, and Su-Wei Chang
- Subjects
Cart ,Linkage disequilibrium ,Multifactor Dimensionality Reduction ,Single-nucleotide polymorphism ,Locus (genetics) ,Biology ,Polymorphism, Single Nucleotide ,Proto-Oncogene Mas ,Linkage Disequilibrium ,Gene interaction ,MDR ,Haplotype ,Genetics ,CART ,Data Mining ,Humans ,Computer Simulation ,Multifactor dimensionality reduction ,Proto-Oncogene Proteins c-ret ,Parkinson Disease ,Regression ,Haplotypes ,Gene–gene interaction ,Regression Analysis ,Algorithms - Abstract
Haplotype-based approaches may have greater power than single-locus analyses when the SNPs are in strong linkage disequilibrium with the risk locus. To overcome potential complexities owing to large numbers of haplotypes in genetic studies, we evaluated two data mining approaches, multifactor dimensionality reduction (MDR) and classification and regression tree (CART), with the concept of haplotypes considering their haplotype uncertainty to detect haplotype–haplotype (HH) interactions. In evaluation of performance for detecting HH interactions, MDR had higher power than CART, but MDR gave a slightly higher type I error. Additionally, we performed an HH interaction analysis with a publicly available dataset of Parkinson's disease and confirmed previous findings that the RET proto-oncogene is associated with the disease. In this study, we showed that using HH interaction analysis is possible to assist researchers in gaining more insight into identifying genetic risk factors for complex diseases.
- Published
- 2010