Article
Licensed
Unlicensed
Requires Authentication
Statistical Significance Threshold Criteria For Analysis of Microarray Gene Expression Data
-
Cheng Cheng
Published/Copyright:
December 19, 2004
The methodological advancement in microarray data analysis on the basis of false discovery rate (FDR) control, such as the q-value plots, allows the investigator to examine the FDR from several perspectives. However, when FDR control at the ``customary" levels 0.01, 0.05, or 0.1 does not provide fruitful findings, there is little guidance for making the trade off between the significance threshold and the FDR level by sound statistical or biological considerations. Thus, meaningful statistical significance criteria that complement the existing FDR methods for large-scale multiple tests are desirable. Three statistical significance criteria, the profile information criterion, the total error proportion, and the guide-gene driven selection, are developed in this research. The first two are general significance threshold criteria for large-scale multiple tests; the profile information criterion is related to the recent theoretical studies of the connection between FDR control and minimax estimation, and the total error proportion is closely related to the asymptotic properties of FDR control in terms of the total error risk. The guide-gene driven selection is an approach to combining statistical significance and the existing biological knowledge of the study at hand. Error properties of these criteria are investigated theoretically and by simulation. The proposed methods are illustrated and compared using an example of genomic screening for novel Arf gene targets. Operating characteristics of q-value and the proposed significance threshold criteria are investigated and compared in a simulation study that employs a model mimicking a gene regulatory pathway. A guideline for using these criteria is provided. Splus/R code is available from the corresponding author upon request.
Keywords: multiple tests; significance threshold selection; profile information criterion; total error proportion; false discovery rate; q-value; microarray; gene expression
Published Online: 2004-12-19
©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston
You are currently not able to access this content.
You are currently not able to access this content.
Articles in the same Issue
- Article
- Using Alpha Wisely: Improving Power to Detect Multiple QTL
- Relating HIV-1 Sequence Variation to Replication Capacity via Trees and Forests
- Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments
- Asymptotic Optimality of Likelihood-Based Cross-Validation
- Using Importance Sampling to Improve Simulation in Linkage Analysis
- Model-Based Assignment and Inference of Protein Backbone Nuclear Magnetic Resonances
- Error-Rate and Decision-Theoretic Methods of Multiple Testing: Which Genes Have High Objective Probabilities of Differential Expression?
- Evaluation of Multiple Models to Distinguish Closely Related Forms of Disease Using DNA Microarray Data: an Application to Multiple Myeloma
- Saturation and Quantization Reduction in Microarray Experiments using Two Scans at Different Sensitivities
- Combining Nearest Neighbor Classifiers Versus Cross-Validation Selection
- Multiple Testing. Part I. Single-Step Procedures for Control of General Type I Error Rates
- Multiple Testing. Part II. Step-Down Procedures for Control of the Family-Wise Error Rate
- Augmentation Procedures for Control of the Generalized Family-Wise Error Rate and Tail Probabilities for the Proportion of False Positives
- Calculating the Statistical Significance of Changes in Pathway Activity From Gene Expression Data
- A Family-Based Association Test for Repeatedly Measured Quantitative Traits Adjusting for Unknown Environmental and/or Polygenic Effects
- Deletion/Substitution/Addition Algorithm in Learning with Applications in Genomics
- Classifying Gene Expression Profiles from Pairwise mRNA Comparisons
- Hierarchical Bayesian Neural Network for Gene Expression Temporal Patterns
- A Mixed Model Approach to Identify Yeast Transcriptional Regulatory Motifs via Microarray Experiments
- Mammalian Genomes Ease Location of Human DNA Functional Segments but Not Their Description
- On the Dependence Structure of Sequence Alignment Scores Calculated with Multiple Scoring Matrices
- Increasing Power for Tests of Genetic Association in the Presence of Phenotype and/or Genotype Error by Use of Double-Sampling
- A Method for Evaluating the Impact of Individual Haplotypes on Disease Incidence in Molecular Epidemiology Studies
- Statistical Methods for Identifying Conserved Residues in Multiple Sequence Alignment
- MergeMaid: R Tools for Merging and Cross-Study Validation of Gene Expression Data
- Sparse Inverse of Covariance Matrix of QTL Effects with Incomplete Marker Data
- Maximum Likelihood for Genome Phylogeny on Gene Content
- Confidence Levels for the Comparison of Microarray Experiments
- PLS Dimension Reduction for Classification with Microarray Data
- Statistical Analysis of Genomic Tag Data
- Statistical Analysis of Adsorption Models for Oligonucleotide Microarrays
- Statistical Significance Threshold Criteria For Analysis of Microarray Gene Expression Data
- A Compendium to Ensure Computational Reproducibility in High-Dimensional Classification Tasks
- Validation and Discovery in Markov Models of Genetics Data
- Making Sense of High-Throughput Protein-Protein Interaction Data
- Reader's Reaction
- Reader Reaction
- Response to Foulkes and De Gruttola
- Software Communication
- BayesMendel: an R Environment for Mendelian Risk Prediction
- Letter to the Editor
- Concerns About Unreliable Data from Spotted cDNA Microarrays Due to Cross-Hybridization and Sequence Errors
Keywords for this article
multiple tests;
significance threshold selection;
profile information criterion;
total error proportion;
false discovery rate;
q-value;
microarray;
gene expression
Articles in the same Issue
- Article
- Using Alpha Wisely: Improving Power to Detect Multiple QTL
- Relating HIV-1 Sequence Variation to Replication Capacity via Trees and Forests
- Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments
- Asymptotic Optimality of Likelihood-Based Cross-Validation
- Using Importance Sampling to Improve Simulation in Linkage Analysis
- Model-Based Assignment and Inference of Protein Backbone Nuclear Magnetic Resonances
- Error-Rate and Decision-Theoretic Methods of Multiple Testing: Which Genes Have High Objective Probabilities of Differential Expression?
- Evaluation of Multiple Models to Distinguish Closely Related Forms of Disease Using DNA Microarray Data: an Application to Multiple Myeloma
- Saturation and Quantization Reduction in Microarray Experiments using Two Scans at Different Sensitivities
- Combining Nearest Neighbor Classifiers Versus Cross-Validation Selection
- Multiple Testing. Part I. Single-Step Procedures for Control of General Type I Error Rates
- Multiple Testing. Part II. Step-Down Procedures for Control of the Family-Wise Error Rate
- Augmentation Procedures for Control of the Generalized Family-Wise Error Rate and Tail Probabilities for the Proportion of False Positives
- Calculating the Statistical Significance of Changes in Pathway Activity From Gene Expression Data
- A Family-Based Association Test for Repeatedly Measured Quantitative Traits Adjusting for Unknown Environmental and/or Polygenic Effects
- Deletion/Substitution/Addition Algorithm in Learning with Applications in Genomics
- Classifying Gene Expression Profiles from Pairwise mRNA Comparisons
- Hierarchical Bayesian Neural Network for Gene Expression Temporal Patterns
- A Mixed Model Approach to Identify Yeast Transcriptional Regulatory Motifs via Microarray Experiments
- Mammalian Genomes Ease Location of Human DNA Functional Segments but Not Their Description
- On the Dependence Structure of Sequence Alignment Scores Calculated with Multiple Scoring Matrices
- Increasing Power for Tests of Genetic Association in the Presence of Phenotype and/or Genotype Error by Use of Double-Sampling
- A Method for Evaluating the Impact of Individual Haplotypes on Disease Incidence in Molecular Epidemiology Studies
- Statistical Methods for Identifying Conserved Residues in Multiple Sequence Alignment
- MergeMaid: R Tools for Merging and Cross-Study Validation of Gene Expression Data
- Sparse Inverse of Covariance Matrix of QTL Effects with Incomplete Marker Data
- Maximum Likelihood for Genome Phylogeny on Gene Content
- Confidence Levels for the Comparison of Microarray Experiments
- PLS Dimension Reduction for Classification with Microarray Data
- Statistical Analysis of Genomic Tag Data
- Statistical Analysis of Adsorption Models for Oligonucleotide Microarrays
- Statistical Significance Threshold Criteria For Analysis of Microarray Gene Expression Data
- A Compendium to Ensure Computational Reproducibility in High-Dimensional Classification Tasks
- Validation and Discovery in Markov Models of Genetics Data
- Making Sense of High-Throughput Protein-Protein Interaction Data
- Reader's Reaction
- Reader Reaction
- Response to Foulkes and De Gruttola
- Software Communication
- BayesMendel: an R Environment for Mendelian Risk Prediction
- Letter to the Editor
- Concerns About Unreliable Data from Spotted cDNA Microarrays Due to Cross-Hybridization and Sequence Errors
