ArticleHuman heredity2009
Exploring the performance of Multifactor Dimensionality Reduction in large scale SNP studies and in the presence of genetic heterogeneity among epistatic disease models.
Article in Human heredity, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- Bevacizumab and Paclitaxel in Advanced, Hormone Receptor-Positive Breast Cancer: Multifactor Dimensionality Reduction Methodology to Identify Best Overall Survival.Oncology research · 2026Observational
- Cluster effect for SNP-SNP interaction pairs for predicting complex traits.Scientific reports · 2024Article
- Common genetic variants associated with melanoma risk or naevus count in patients with wildtype MC1R melanoma.The British journal of dermatology · 2022Article
- Examining SNP-SNP interactions and risk of clinical outcomes in colorectal cancer using multifactor dimensionality reduction based methods.Frontiers in genetics · 2022Article
- Non-additive effects of ACVR2A in preeclampsia in a Philippine population.BMC pregnancy and childbirth · 2019Article
- Investigating Gene-Gene and Gene-Environment Interactions in the Association Between Overnutrition and Obesity-Related Phenotypes.Frontiers in genetics · 2019Article
- Genetic interaction of P2X7 receptor and VEGFR-2 polymorphisms identifies a favorable prognostic profile in prostate cancer patients.Oncotarget · 2015Article
- Considerations for Using Genetic and Epigenetic Information in Occupational Health Risk Assessment and Standard Setting.Journal of occupational and environmental hygiene · 2015Article
- Bridging the gap between statistical and biological epistasis in Alzheimer's disease.BioMed research international · 2015Review
- Association between risk of oral precancer and genetic variations in microRNA and related processing genes.Journal of biomedical science · 2014Article
- An omnibus permutation test on ensembles of two-locus analyses can detect pure epistasis and genetic heterogeneity in genome-wide association studies.SpringerPlus · 2013Article
- Genetics of Alzheimer's disease.BioMed research international · 2013Review
- A comparison of internal model validation methods for multifactor dimensionality reduction in the case of genetic heterogeneity.BMC research notes · 2012Article
- Predicting the difficulty of pure, strict, epistatic models: metrics for simulated model selection.BioData mining · 2012Article
- Vitamin D receptor gene as a candidate gene for Parkinson disease.Annals of human genetics · 2011Article
- Multifactor dimensionality reduction as a filter-based approach for genome wide association studies.Frontiers in genetics · 2011Article
- A screening methodology based on Random Forests to improve the detection of gene-gene interactions.European journal of human genetics : EJHG · 2010Article
- Survival dimensionality reduction (SDR): development and clinical application of an innovative approach to detect epistasis in presence of right-censored data.BMC bioinformatics · 2010Article
- A general framework for formal tests of interaction after exhaustive search methods with applications to MDR and MDR-PDT.PloS one · 2010Article
- Methods for investigating gene-environment interactions in candidate pathway and genome-wide association studies.Annual review of public health · 2010Review
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5 authors.
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No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND/
aimsIn genetic studies of complex disease a consideration for the investigator is detection of joint effects. The Multifactor Dimensionality Reduction (MDR) algorithm searches for these effects with an exhaustive approach. Previously unknown aspects of MDR performance were the power to detect interactive effects given large numbers of non-model loci or varying degrees of heterogeneity among multiple epistatic disease models.
methodsTo address the performance with many non-model loci, datasets of 500 cases and 500 controls with 100 to 10,000 SNPs were simulated for two-locus models, and one hundred 500-case/500-control datasets with 100 and 500 SNPs were simulated for three-locus models. Multiple levels of locus heterogeneity were simulated in several sample sizes.
resultsThese results show MDR is robust to locus heterogeneity when the definition of power is not as conservative as in previous simulation studies where all model loci were required to be found by the method. The results also indicate that MDR performance is related more strongly to broad-sense heritability than sample size and is not greatly affected by non-model loci.
conclusionsA study in which a population with high heritability estimates is sampled predisposes the MDR study to success more than a larger ascertainment in a population with smaller estimates.
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