Testing for Gene-Gene Interaction with AMMI Models
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Amina Barhdadi
Studies have shown that many common diseases are influenced by multiple genes and their interactions. There is currently a strong interest in testing for association between combinations of these genes and disease, in particular because genes that affect the risk of disease only in the presence of another genetic variant may not be detected in marginal analysis. In this paper we propose the use of additive main effect and multiplicative interaction (AMMI) models to detect and to quantify gene-gene interaction effects for a quantitative trait. The objective of the present research is to demonstrate the practical advantages of these models to describe complex interaction between two unlinked loci. Although gene-gene interactions have often been defined as a deviance from additive genetic effects, the residual term has generally not been appropriately treated. The AMMI models allow for the analysis of a two way factorial data structure and combine the analysis of variance of the two main genotype effects with a principal component analysis of the residual multiplicative interaction. The AMMI models for gene-gene interaction presented here allow for the testing of non additivity between the two loci, and also describe how their interaction structure fits the existing non-additivity. Moreover, these models can be used to identify the specific two genotypes combinations that contribute to the significant gene-gene interaction. We describe the use of the biplot to display the structure of the interaction and evaluate the performance of the AMMI and the special cases of the AMMI previously described by Tukey and Mandel with simulated data sets. Our simulated study showed that the AMMI model is as powerful as general linear models when the interaction is not modeled in the presence of marginal effects. However, in the presence of pure epitasis, i.e. in the absence of marginal effects, the AMMI method was not found to be superior to other tested regression methods.
©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston
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Articles in the same Issue
- Article
- Epistatic Interactions
- Testing for Gene-Gene Interaction with AMMI Models
- A Bayesian Hierarchical Model for Quantitative Real-Time PCR Data
- Informative or Noninformative Calls for Gene Expression: A Latent Variable Approach
- Detecting Genotyping Error Using Measures of Degree of Hardy-Weinberg Disequilibrium
- Optimisation of HMM Topologies Enhances DNA and Protein Sequence Modelling
- The Apportionment of Total Genetic Variation by Categorical Analysis of Variance
- Dealing with Heterogeneity between Cohorts in Genomewide SNP Association Studies
- An Empirical Bayesian Method for Estimating Biological Networks from Temporal Microarray Data
- Parameter Estimation in Multiple-Hidden I.I.D. Models from Biological Multiple Alignment
- Asymptotic Distribution of the "Orthogonal" Quantitative Transmission Disequilibrium Test in a Structured Population: Exact Formula
- Comparing Spatial Maps of Human Population-Genetic Variation Using Procrustes Analysis
- An Internal Calibration Method for Protein-Array Studies
- Weighted-LASSO for Structured Network Inference from Time Course Data
- Trilocus Disequilibrium Analysis of Multiallelic Markers in Outcrossing Populations
- Sparse Partial Least Squares Classification for High Dimensional Data
- Reconstructability Analysis as a Tool for Identifying Gene-Gene Interactions in Studies of Human Diseases
- Sub-Modular Resolution Analysis by Network Mixture Models
- Space Oriented Rank-Based Data Integration
- The Generalized Odds Ratio as a Measure of Genetic Risk Effect in the Analysis and Meta-Analysis of Association Studies
- Network Enrichment Analysis in Complex Experiments
- Shrinkage Estimation of Effect Sizes as an Alternative to Hypothesis Testing Followed by Estimation in High-Dimensional Biology: Applications to Differential Gene Expression
- Buckley-James Boosting for Survival Analysis with High-Dimensional Biomarker Data
- A Random Coefficients Model for Regional Co-Expression Associated with DNA Copy Number
- Locating Multiple Interacting Quantitative Trait Loci with the Zero-Inflated Generalized Poisson Regression
- Classification of Genomic Sequences via Wavelet Variance and a Self-Organizing Map with an Application to Mitochondrial DNA
- Confidently Estimating the Number of DNA Replication Origins
- Generalizing Moving Averages for Tiling Arrays Using Combined P-Value Statistics
- Lasso Logistic Regression, GSoft and the Cyclic Coordinate Descent Algorithm: Application to Gene Expression Data
- Granger Causality Analysis of Human Cell-Cycle Gene Expression Profiles
- Mapping Quantitative Trait Loci in a Non-Equilibrium Population
- On the Optimal Design of Genetic Variant Discovery Studies
- On Optimal Selection of Summary Statistics for Approximate Bayesian Computation
- Assessment of LD Matrix Measures for the Analysis of Biological Pathway Association
- Optimal Tests Shrinking Both Means and Variances Applicable to Microarray Data Analysis
- The Detection of Blur in Affymetrix GeneChips
- Regression-Based Multi-Trait QTL Mapping Using a Structural Equation Model
- Spatial Clustering of Array CGH Features in Combination with Hierarchical Multiple Testing
- Predicting Patient Survival from Longitudinal Gene Expression
- Including Probe-Level Measurement Error in Robust Mixture Clustering of Replicated Microarray Gene Expression
- Reader's Reaction
- An Alternative Model of Type A Dependence in a Gene Set of Correlated Genes
- Letter to the Editor
- Permutation P-values Should Never Be Zero: Calculating Exact P-values When Permutations Are Randomly Drawn
