A Unification of Multivariate Methods for Meta-Analysis of Genetic Association Studies
Methods for multivariate meta-analysis of genetic association studies are reviewed, summarized and presented in a unified framework. Modifications of standard models are described in detail in order to be applied in genetic association studies. The model based on summary data is uniformly defined for both discrete and continuous outcomes and analytical expressions for the covariance of the two jointly modeled outcomes are derived for both cases. The models based on the binary nature of the data are fitted using both prospective and retrospective likelihood. Furthermore, formal tests for assessing the genetic model of inheritance are developed based on standard normal theory. The general model is compared to the recently proposed genetic model-free bivariate approach (either using summary or binary data), and it is clearly shown that the estimates provided by this approach are nearly identical to the estimates derived by the general bivariate model using the aforementioned tests for the genetic model. The methods developed here as well as the tests, are easily implemented in all major statistical packages, escaping the need of self written software. The methods are applied in several already published meta-analyses of genetic association studies (with both discrete and continuous outcomes) and the results are compared against the widely used univariate approach as well as against the genetic model free approaches. Illustrative examples of code in Stata are given in the appendix. It is anticipated that the methods developed in this work will be widely applied in the meta-analysis of genetic association studies.
©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston
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Artikel in diesem Heft
- Article
- Self-Organizing Maps with Statistical Phase Synchronization (SOMPS) for Analyzing Cell Cycle-Specific Gene Expression Data
- Coalescent Time Distributions in Trees of Arbitrary Size
- Quantifying the Association between Gene Expressions and DNA-Markers by Penalized Canonical Correlation Analysis
- Nonparametric Functional Mapping of Quantitative Trait Loci Underlying Programmed Cell Death
- Accommodating Uncertainty in a Tree Set for Function Estimation
- Drifting Markov Models with Polynomial Drift and Applications to DNA Sequences
- Comparing the Characteristics of Gene Expression Profiles Derived by Univariate and Multivariate Classification Methods
- Calculating Confidence Intervals for Prediction Error in Microarray Classification Using Resampling
- Structure Learning in Nested Effects Models
- Correcting the Estimated Level of Differential Expression for Gene Selection Bias: Application to a Microarray Study
- Adapting Prediction Error Estimates for Biased Complexity Selection in High-Dimensional Bootstrap Samples
- Adaptive Choice of the Number of Bootstrap Samples in Large Scale Multiple Testing
- Re-Cracking the Nucleosome Positioning Code
- Semi-Parametric Differential Expression Analysis via Partial Mixture Estimation
- A SNP Streak Model for the Identification of Genetic Regions Identical-by-descent
- Detecting Two-Locus Gene-Gene Effects Using Monotonisation of the Penetrance Matrix
- Modeling DNA Methylation in a Population of Cancer Cells
- Phenotyping Genetic Diseases Using an Extension of µ-Scores for Multivariate Data
- The Estimator of the Optimal Measure of Allelic Association: Mean, Variance and Probability Distribution When the Sample Size Tends to Infinity
- Predicting Protein Concentrations with ELISA Microarray Assays, Monotonic Splines and Monte Carlo Simulation
- A Comparison of Normalization Techniques for MicroRNA Microarray Data
- Collapsing SNP Genotypes in Case-Control Genome-Wide Association Studies Increases the Type I Error Rate and Power
- Estimating Number of Clusters Based on a General Similarity Matrix with Application to Microarray Data
- Data Distribution of Short Oligonucleotide Expression Arrays and Its Application to the Construction of a Generalized Intellectual Framework
- Approximately Sufficient Statistics and Bayesian Computation
- A Composite-Conditional-Likelihood Approach for Gene Mapping Based on Linkage Disequilibrium in Windows of Marker Loci
- Statistical Methods in Integrative Analysis for Gene Regulatory Modules
- Reducing Spatial Flaws in Oligonucleotide Arrays by Using Neighborhood Information
- Pattern Classification of Phylogeny Signals
- A Unification of Multivariate Methods for Meta-Analysis of Genetic Association Studies
- Importance Sampling for the Infinite Sites Model
- Supervised Distance Matrices
- Addressing the Shortcomings of Three Recent Bayesian Methods for Detecting Interspecific Recombination in DNA Sequence Alignments
- A Sparse PLS for Variable Selection when Integrating Omics Data
- Software Communication
- TRAB: Testing Whether Mutation Frequencies Are Above an Unknown Background
