ArticleAnnals of human genetics2011
A robust multifactor dimensionality reduction method for detecting gene-gene interactions with application to the genetic analysis of bladder cancer susceptibility.
Article in Annals of human genetics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.
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Who cites it
32 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pathway-based genetic analysis of preterm birth.Genomics · 2013Pooled it
- eNOS and BDKRB2 genotypes affect the antihypertensive responses to enalapril.European journal of clinical pharmacology · 2013Trial
- Investigating the Differential Impact of Psychosocial Factors by Patient Characteristics and Demographics on Veteran Suicide Risk Through Machine Learning Extraction of Cross-Modal Interactions.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2025Article
- Functional polymorphisms ofFrontiers in genetics · 2024Article
- Overview of frequent pattern mining.Genomics & informatics · 2022Article
- Spatial rank-based multifactor dimensionality reduction to detect gene-gene interactions for multivariate phenotypes.BMC bioinformatics · 2021Article
- Hereditary and breastfeeding factors are positively associated with the aetiology of mammary gland hyperplasia: a case-control study.International health · 2021Article
- Utilizing machine learning dimensionality reduction for risk stratification of chest pain patients in the emergency department.BMC medical research methodology · 2021Article
- Genetic interactions effects for cancer disease identification using computational models: a review.Medical & biological engineering & computing · 2021Review
- Interaction Between NOS3 and HMOX1 on Antihypertensive Drug Responsiveness in Preeclampsia.Revista brasileira de ginecologia e obstetricia : revista da Federacao Brasileira das Sociedades de Ginecologia e Obstetricia · 2020Article
- CHIMGEN: a Chinese imaging genetics cohort to enhance cross-ethnic and cross-geographic brain research.Molecular psychiatry · 2020Review
- Epistasis of polymorphisms related to the articular cartilage extracellular matrix in knee osteoarthritis: Analysis-based multifactor dimensionality reduction.Genetics and molecular biology · 2020Article
- Gene-gene interaction: the curse of dimensionality.Annals of translational medicine · 2019Review
- Gene-gene interactions in the NAMPT pathway, plasma visfatin/NAMPT levels, and antihypertensive therapy responsiveness in hypertensive disorders of pregnancy.The pharmacogenomics journal · 2017Article
- KNN-MDR: a learning approach for improving interactions mapping performances in genome wide association studies.BMC bioinformatics · 2017Article
- An empirical fuzzy multifactor dimensionality reduction method for detecting gene-gene interactions.BMC genomics · 2017Article
- A roadmap to multifactor dimensionality reduction methods.Briefings in bioinformatics · 2016Review
- An efficiency analysis of high-order combinations of gene-gene interactions using multifactor-dimensionality reduction.BMC genomics · 2015Article
- Tissue inhibitor of matrix metalloproteinase-1 polymorphism, plasma TIMP-1 levels, and antihypertensive therapy responsiveness in hypertensive disorders of pregnancy.The pharmacogenomics journal · 2014Article
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7 authors.
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Abstract
A central goal of human genetics is to identify susceptibility genes for common human diseases. An important challenge is modelling gene-gene interaction or epistasis that can result in nonadditivity of genetic effects. The multifactor dimensionality reduction (MDR) method was developed as a machine learning alternative to parametric logistic regression for detecting interactions in the absence of significant marginal effects. The goal of MDR is to reduce the dimensionality inherent in modelling combinations of polymorphisms using a computational approach called constructive induction. Here, we propose a Robust Multifactor Dimensionality Reduction (RMDR) method that performs constructive induction using a Fisher's Exact Test rather than a predetermined threshold. The advantage of this approach is that only statistically significant genotype combinations are considered in the MDR analysis. We use simulation studies to demonstrate that this approach will increase the success rate of MDR when there are only a few genotype combinations that are significantly associated with case-control status. We show that there is no loss of success rate when this is not the case. We then apply the RMDR method to the detection of gene-gene interactions in genotype data from a population-based study of bladder cancer in New Hampshire.
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