Computing Asymptotic Power and Sample Size for Case-Control Genetic Association Studies in the Presence of Phenotype and/or Genotype Misclassification Errors
-
Fei Ji
It is well established that phenotype and genotype misclassification errors reduce the power to detect genetic association. Resampling a subset of the data (e.g, double-sampling) of genotype and/or phenotype with a gold standard measurement is one method to address this issue. We derive the non-centrality parameter (NCP) for the recently published Likelihood Ratio Test Allowing for Error (LRTae) in the presence of random phenotype and genotype errors. With the NCP, power and sample size can be analytically determined at any significance level. We verify analytic power with simulations using a 2**k factorial design given high and low settings of: case and control genotype frequencies, phenotype and genotype misclassification probabilities, total sample size, ratio of cases to controls, and proportions of phenotype and/or genotype double-samples. We also perform example applications of our method assuming equal costs for the LRTae method and the standard method that does not use double-sample information (LRTstd) to determine if power gain due to double-sampling a proportion of samples outweighs the reduction in sample size due to additional costs in obtaining double-samples.Our results showed a median difference of at most 0.01 between analytic and simulation power for the factorial design settings, with maximum difference of 0.054. For our cost/benefits analysis calculations, results for genotype errors are that double-sampling appears most beneficial (in terms of power gain) when cost of double-sampling is relatively low, irrespective of the proportion of individuals double-sampled. In the presence of phenotype error, there is always power gain using the LRTae method for the parameter settings considered. We have freely available software that performs power and sample size calculations for the LRTae method and cost/benefits analyses comparing power for LRTae and LRTstd methods assuming equal costs.
©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston
Articles in the same Issue
- Article
- Estimating Motifs Under Order Restrictions
- Reproducible Research: A Bioinformatics Case Study
- Generalized Rank Tests for Replicated Microarray Data
- Stepwise Normalization of Two-Channel Spotted Microarrays
- Comparing Automatic and Manual Image Processing in FLARE Assay Analysis for Colon Carcinogenesis
- Pixel-level Signal Modelling with Spatial Correlation for Two-Colour Microarrays
- Empirical Bayes Microarray ANOVA and Grouping Cell Lines by Equal Expression Levels
- Multiple Testing and Data Adaptive Regression: An Application to HIV-1 Sequence Data.
- Early Diagnostic Marker Panel Determination for Microarray Based Clinical Studies
- Prediction of Missing Values in Microarray and Use of Mixed Models to Evaluate the Predictors
- Combined Association and Linkage Analysis for General Pedigrees and Genetic Models
- Incorporating Biological Information as a Prior in an Empirical Bayes Approach to Analyzing Microarray Data
- The Relative Inefficiency of Sequence Weights Approaches in Determining a Nucleotide Position Weight Matrix
- A Simple Loglinear Model for Haplotype Effects in a Case-Control Study Involving Two Unphased Genotypes
- Extension of the SIMLA Package for Generating Pedigrees with Complex Inheritance Patterns: Environmental Covariates, Gene-Gene and Gene-Environment Interaction
- Error Distribution for Gene Expression Data
- A General Framework for Weighted Gene Co-Expression Network Analysis
- Statistical Inference in Evolutionary Models of DNA Sequences via the EM Algorithm
- Comparing Bacterial DNA Microarray Fingerprints
- Continuous Covariates in Genetic Association Studies of Case-Parent Triads: Gene and Gene-Environment Interaction Effects, Population Stratification, and Power Analysis
- Robust Remote Homology Detection by Feature Based Profile Hidden Markov Models
- Empirical Bayes Estimation of a Sparse Vector of Gene Expression Changes
- Hierarchical Inverse Gaussian Models and Multiple Testing: Application to Gene Expression Data
- FADO: A Statistical Method to Detect Favored or Avoided Distances between Occurrences of Motifs using the Hawkes' Model
- Prediction of Genomewide Conserved Epitope Profiles of HIV-1: Classifier Choice and Peptide Representation
- Fold-Change Estimation of Differentially Expressed Genes using Mixture Mixed-Model
- Test on the Structure of Biological Sequences via Chaos Game Representation
- Reverse Engineering Galactose Regulation in Yeast through Model Selection
- Empirical Bayes and Resampling Based Multiple Testing Procedure Controlling Tail Probability of the Proportion of False Positives.
- Weighted Analysis of Paired Microarray Experiments
- A Probabilistic Approach to Large-Scale Association Scans: A Semi-Bayesian Method to Detect Disease-Predisposing Alleles
- A Shrinkage Approach to Large-Scale Covariance Matrix Estimation and Implications for Functional Genomics
- Structured Antedependence Models for Functional Mapping of Multiple Longitudinal Traits
- Correlation Between Gene Expression Levels and Limitations of the Empirical Bayes Methodology for Finding Differentially Expressed Genes
- Bayesian Statistical Studies of the Ramachandran Distribution
- On Reference Designs For Microarray Experiments
- Computing Asymptotic Power and Sample Size for Case-Control Genetic Association Studies in the Presence of Phenotype and/or Genotype Misclassification Errors
Articles in the same Issue
- Article
- Estimating Motifs Under Order Restrictions
- Reproducible Research: A Bioinformatics Case Study
- Generalized Rank Tests for Replicated Microarray Data
- Stepwise Normalization of Two-Channel Spotted Microarrays
- Comparing Automatic and Manual Image Processing in FLARE Assay Analysis for Colon Carcinogenesis
- Pixel-level Signal Modelling with Spatial Correlation for Two-Colour Microarrays
- Empirical Bayes Microarray ANOVA and Grouping Cell Lines by Equal Expression Levels
- Multiple Testing and Data Adaptive Regression: An Application to HIV-1 Sequence Data.
- Early Diagnostic Marker Panel Determination for Microarray Based Clinical Studies
- Prediction of Missing Values in Microarray and Use of Mixed Models to Evaluate the Predictors
- Combined Association and Linkage Analysis for General Pedigrees and Genetic Models
- Incorporating Biological Information as a Prior in an Empirical Bayes Approach to Analyzing Microarray Data
- The Relative Inefficiency of Sequence Weights Approaches in Determining a Nucleotide Position Weight Matrix
- A Simple Loglinear Model for Haplotype Effects in a Case-Control Study Involving Two Unphased Genotypes
- Extension of the SIMLA Package for Generating Pedigrees with Complex Inheritance Patterns: Environmental Covariates, Gene-Gene and Gene-Environment Interaction
- Error Distribution for Gene Expression Data
- A General Framework for Weighted Gene Co-Expression Network Analysis
- Statistical Inference in Evolutionary Models of DNA Sequences via the EM Algorithm
- Comparing Bacterial DNA Microarray Fingerprints
- Continuous Covariates in Genetic Association Studies of Case-Parent Triads: Gene and Gene-Environment Interaction Effects, Population Stratification, and Power Analysis
- Robust Remote Homology Detection by Feature Based Profile Hidden Markov Models
- Empirical Bayes Estimation of a Sparse Vector of Gene Expression Changes
- Hierarchical Inverse Gaussian Models and Multiple Testing: Application to Gene Expression Data
- FADO: A Statistical Method to Detect Favored or Avoided Distances between Occurrences of Motifs using the Hawkes' Model
- Prediction of Genomewide Conserved Epitope Profiles of HIV-1: Classifier Choice and Peptide Representation
- Fold-Change Estimation of Differentially Expressed Genes using Mixture Mixed-Model
- Test on the Structure of Biological Sequences via Chaos Game Representation
- Reverse Engineering Galactose Regulation in Yeast through Model Selection
- Empirical Bayes and Resampling Based Multiple Testing Procedure Controlling Tail Probability of the Proportion of False Positives.
- Weighted Analysis of Paired Microarray Experiments
- A Probabilistic Approach to Large-Scale Association Scans: A Semi-Bayesian Method to Detect Disease-Predisposing Alleles
- A Shrinkage Approach to Large-Scale Covariance Matrix Estimation and Implications for Functional Genomics
- Structured Antedependence Models for Functional Mapping of Multiple Longitudinal Traits
- Correlation Between Gene Expression Levels and Limitations of the Empirical Bayes Methodology for Finding Differentially Expressed Genes
- Bayesian Statistical Studies of the Ramachandran Distribution
- On Reference Designs For Microarray Experiments
- Computing Asymptotic Power and Sample Size for Case-Control Genetic Association Studies in the Presence of Phenotype and/or Genotype Misclassification Errors
