Multifactor Dimensionality Reduction
An R package implementation of multifactor dimensionality reduction
... is Multifactor Dimensionality Reduction (MDR), a non- parametric exhaustive search method that considers all combinations of potentially interacting loci and classifies individuals to disease status ...
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Multifactor dimensionality reduction reveals a three-locus epistatic interaction associated with susceptibility to pulmonary tuberculosis
... Background: Identifying high-order genetics associations with non-additive (i.e. epistatic) effects in population-based studies of common human diseases is a computational challenge. Multifactor ...
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Unified Cox model based multifactor dimensionality reduction method for gene-gene interaction analysis of the survival phenotype
... Background: One strategy for addressing missing heritability in genome-wide association study is gene-gene interaction analysis, which, unlike a single gene approach, involves high-dimensionality. The ...
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Multifactor dimensionality reduction: An analysis strategy for modelling and detecting gene - gene interactions in human genetics and pharmacogenomics studies
... The dimensionality involved in the evaluation of combinations of many such variables quickly diminishes the usefulness of traditional, parametric statistical ...methods. Multifactor dimensionality ...
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A robustness study of parametric and non-parametric tests in model-based multifactor dimensionality reduction for epistasis detection
... data dimensionality reduction method for quantitative traits (generalized MDR - GMDR) [35] is based on score statis- tics to define differential multilocus genotype groups related to the trait of ...2-locus ...
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Fuzzy set-based generalized multifactor dimensionality reduction analysis of gene-gene interactions
... heritability. Multifactor dimensionality reduction (MDR) is one of most commonly used methods for GGI ...generalized multifactor dimensionality reduction (GMDR) method is an ...
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Multifactor dimensionality reduction analysis identifies specific nucleotide patterns promoting genetic polymorphisms
... Results: We modeled the relationship between DNA sequence and observed polymorphisms using the novel multifactor dimensionality reduction (MDR) approach. MDR was originally developed to detect ...
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Risk score modeling of multiple gene to gene interactions using aggregated-multifactor dimensionality reduction
... Aggregated-Multifactor Dimensionality Reduction (A-MDR) method that exhaustively searches for statistically significant gene-gene (GxG) interactions to generate a gene interaction ...
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Global tests of P-values for multifactor dimensionality reduction models in selection of optimal number of target genes
... Multifactor Dimensionality Reduction (MDR) is a novel statistical method developed to characterize and detect nonlinear complex gene-gene interactions (epistasis) that could be associated with ...
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The effect of alternative permutation testing strategies on the performance of multifactor dimensionality reduction
... Multifactor Dimensionality Reduction (MDR) is one such method [10]. MDR was designed to detect interactions in categorical independent variables and a dichotomous dependent variable (i.e. ...
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Identification of interactions using model based multifactor dimensionality reduction
... Model-based multifactor dimensionality reduction (MB-MDR), a semiparametric machine learning method allowing adjustment for confounding variables and lower level effects, is applied to Genetic ...
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Software for detecting gene-gene interactions using Multifactor Dimensionality Reduction: Introducing the R package MDR
... Ritchie MD, Hahn LW, Roodi N, Bailey LR, Dupont WD, Parl FF, Moore JH. 2001. Multifactor-‐dimensionality reduction reveals high-‐order interactions among estrogen-‐metabolism genes in sporadic ...
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Identifying gene-gene interactions that are highly associated with Body Mass Index using Quantitative Multifactor Dimensionality Reduction (QMDR)
... Using the set of SNPs that emerged from the main effect filter, QMDR analysis identified seven novel SNP-SNP interaction models that were associated with BMI (Bonferroni corrected P- val[r] ...
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A comparison of internal model validation methods for multifactor dimensionality reduction in the case of genetic heterogeneity
... MDR is a widely used data mining technique that per- forms an exhaustive search of all possible genes and combinations of genes to find the best model for a cer- tain genetic trait [23]. It is able to accommodate more ...
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Identification of epistatic interactions through genome-wide association studies in sporadic medullary and juvenile papillary thyroid carcinomas
... the Multifactor-dimensionality reduction (MDR) method ...the dimensionality of SNP data improving the identification of combinations of polymorphisms associated with disease ...the ...
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Vitamin D receptor gene polymorphisms are associated with triceps skin fold thickness and body fat percentage but not with body mass index or waist circumference in Han Chinese
... General multifactor dimensionality reduction; HDL- C: High-density lipoprotein cholesterol; HWE: Hardy-Weinberg equilibrium; LD: Linkage disequilibrium; LDL-C: Low-density lipoprotein cholesterol; ...
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A 2-Dimensional Gabor-Filters for Face Recognition System: A Survey
... supervised dimensionality reduction method also called Fisher’s Linear Discriminant ...out reduction of dimensions while preserving as much of the class discriminatory information as ...This ...
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Linear Dimensionality Reduction: Survey, Insights, and Generalizations
... to dimensionality reduction, in that it uses a lower dimensional set of factors to reconstruct noisy or missing high-dimensional data (for example, classical latent semantic indexing is entirely equivalent ...
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Dimensionality Reduction for Handwritten Digit Recognition
... a dimensionality reduction tech- nique which looks to the best possible way to dis- criminate between classes in the underlying subspace rather than discriminating based on data ...
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Dimensionality reduction for parametric design exploration
... Dimensionality reduction has strong links to research in neuroscience and cognition, for example, in mapping sensory experience to associated three- dimensional locations in the brain, the so-called ...
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