Optimality Criteria for the Design of 2-Color Microarray Studies
-
Kathleen F. Kerr
We discuss the definition and application of design criteria for evaluating the efficiency of 2-color microarray designs. First, we point out that design optimality criteria are defined differently for the regression and block design settings. This has caused some confusion in the literature and warrants clarification. Linear models for microarray data analysis have equivalent formulations as ANOVA or regression models. However, this equivalence does not extend to design criteria. We discuss optimality criterion, and argue against applying regression-style D-optimality to the microarray design problem. We further disfavor E- and D-optimality (as defined in block design) because they are not attuned to scientific questions of interest.
©2012 Walter de Gruyter GmbH & Co. KG, Berlin/Boston
Artikel in diesem Heft
- Article
- The Inheritance Procedure: Multiple Testing of Tree-structured Hypotheses
- Optimality Criteria for the Design of 2-Color Microarray Studies
- Stopping-Time Resampling and Population Genetic Inference under Coalescent Models
- A Mixture-Model Approach for Parallel Testing for Unequal Variances
- Fast Identification of Biological Pathways Associated with a Quantitative Trait Using Group Lasso with Overlaps
- MicroRNA Transcription Start Site Prediction with Multi-objective Feature Selection
- A Context Dependent Pair Hidden Markov Model for Statistical Alignment
- Fast Wavelet Based Functional Models for Transcriptome Analysis with Tiling Arrays
- Alignment-free Sequence Comparison for Biologically Realistic Sequences of Moderate Length
- Transcriptional Network Inference from Functional Similarity and Expression Data: A Global Supervised Approach
- Improving Hidden Markov Models for Classification of Human Immunodeficiency Virus-1 Subtypes through Linear Classifier Learning
Artikel in diesem Heft
- Article
- The Inheritance Procedure: Multiple Testing of Tree-structured Hypotheses
- Optimality Criteria for the Design of 2-Color Microarray Studies
- Stopping-Time Resampling and Population Genetic Inference under Coalescent Models
- A Mixture-Model Approach for Parallel Testing for Unequal Variances
- Fast Identification of Biological Pathways Associated with a Quantitative Trait Using Group Lasso with Overlaps
- MicroRNA Transcription Start Site Prediction with Multi-objective Feature Selection
- A Context Dependent Pair Hidden Markov Model for Statistical Alignment
- Fast Wavelet Based Functional Models for Transcriptome Analysis with Tiling Arrays
- Alignment-free Sequence Comparison for Biologically Realistic Sequences of Moderate Length
- Transcriptional Network Inference from Functional Similarity and Expression Data: A Global Supervised Approach
- Improving Hidden Markov Models for Classification of Human Immunodeficiency Virus-1 Subtypes through Linear Classifier Learning
