Biomaterial Database

Flexible empirical Bayes models for differential gene expression. 2007

Kenneth Lo, and Raphael Gottardo

Department of Statistics, University of British Columbia, 333-6356 Agricultural Road, Vancouver, BC, Canada V6T 1Z2. c.lo@stat.ubc.ca

BACKGROUND Inference about differential expression is a typical objective when analyzing gene expression data. Recently, Bayesian hierarchical models have become increasingly popular for this type of problem. The two most common hierarchical models are the hierarchical Gamma-Gamma (GG) and Lognormal-Normal (LNN) models. However, to facilitate inference, some unrealistic assumptions have been made. One such assumption is that of a common coefficient of variation across genes, which can adversely affect the resulting inference. RESULTS In this paper, we extend both the GG and LNN modeling frameworks to allow for gene-specific variances and propose EM based algorithms for parameter estimation. The proposed methodology is evaluated on three experimental datasets: one cDNA microarray experiment and two Affymetrix spike-in experiments. The two extended models significantly reduce the false positive rate while keeping a high sensitivity when compared to the originals. Finally, using a simulation study we show that the new frameworks are also more robust to model misspecification. BACKGROUND The R code for implementing the proposed methodology can be downloaded at http://www.stat.ubc.ca/~c.lo/FEBarrays. BACKGROUND The supplementary material is available at http://www.stat.ubc.ca/~c.lo/FEBarrays/supp.pdf.

UI	MeSH Term	Description	Entries
D008957	Models, Genetic	Theoretical representations that simulate the behavior or activity of genetic processes or phenomena. They include the use of mathematical equations, computers, and other electronic equipment.	Genetic Models,Genetic Model,Model, Genetic
D003627	Data Interpretation, Statistical	Application of statistical procedures to analyze specific observed or assumed facts from a particular study.	Data Analysis, Statistical,Data Interpretations, Statistical,Interpretation, Statistical Data,Statistical Data Analysis,Statistical Data Interpretation,Analyses, Statistical Data,Analysis, Statistical Data,Data Analyses, Statistical,Interpretations, Statistical Data,Statistical Data Analyses,Statistical Data Interpretations
D000465	Algorithms	A procedure consisting of a sequence of algebraic formulas and/or logical steps to calculate or determine a given task.	Algorithm
D001499	Bayes Theorem	A theorem in probability theory named for Thomas Bayes (1702-1761). In epidemiology, it is used to obtain the probability of disease in a group of people with some characteristic on the basis of the overall rate of that disease and of the likelihood of that characteristic in healthy and diseased individuals. The most familiar application is in clinical decision analysis where it is used for estimating the probability of a particular diagnosis given the appearance of some symptoms or test result.	Bayesian Analysis,Bayesian Estimation,Bayesian Forecast,Bayesian Method,Bayesian Prediction,Analysis, Bayesian,Bayesian Approach,Approach, Bayesian,Approachs, Bayesian,Bayesian Approachs,Estimation, Bayesian,Forecast, Bayesian,Method, Bayesian,Prediction, Bayesian,Theorem, Bayes
D015233	Models, Statistical	Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc.	Probabilistic Models,Statistical Models,Two-Parameter Models,Model, Statistical,Models, Binomial,Models, Polynomial,Statistical Model,Binomial Model,Binomial Models,Model, Binomial,Model, Polynomial,Model, Probabilistic,Model, Two-Parameter,Models, Probabilistic,Models, Two-Parameter,Polynomial Model,Polynomial Models,Probabilistic Model,Two Parameter Models,Two-Parameter Model
D016015	Logistic Models	Statistical models which describe the relationship between a qualitative dependent variable (that is, one which can take only certain discrete values, such as the presence or absence of a disease) and an independent variable. A common application is in epidemiology for estimating an individual's risk (probability of a disease) as a function of a given risk factor.	Logistic Regression,Logit Models,Models, Logistic,Logistic Model,Logistic Regressions,Logit Model,Model, Logistic,Model, Logit,Models, Logit,Regression, Logistic,Regressions, Logistic
D020411	Oligonucleotide Array Sequence Analysis	Hybridization of a nucleic acid sample to a very large set of OLIGONUCLEOTIDE PROBES, which have been attached individually in columns and rows to a solid support, to determine a BASE SEQUENCE, or to detect variations in a gene sequence, GENE EXPRESSION, or for GENE MAPPING.	DNA Microarrays,Gene Expression Microarray Analysis,Oligonucleotide Arrays,cDNA Microarrays,DNA Arrays,DNA Chips,DNA Microchips,Gene Chips,Oligodeoxyribonucleotide Array Sequence Analysis,Oligonucleotide Microarrays,Sequence Analysis, Oligonucleotide Array,cDNA Arrays,Array, DNA,Array, Oligonucleotide,Array, cDNA,Arrays, DNA,Arrays, Oligonucleotide,Arrays, cDNA,Chip, DNA,Chip, Gene,Chips, DNA,Chips, Gene,DNA Array,DNA Chip,DNA Microarray,DNA Microchip,Gene Chip,Microarray, DNA,Microarray, Oligonucleotide,Microarray, cDNA,Microarrays, DNA,Microarrays, Oligonucleotide,Microarrays, cDNA,Microchip, DNA,Microchips, DNA,Oligonucleotide Array,Oligonucleotide Microarray,cDNA Array,cDNA Microarray
D020869	Gene Expression Profiling	The determination of the pattern of genes expressed at the level of GENETIC TRANSCRIPTION, under specific circumstances or in a specific cell.	Gene Expression Analysis,Gene Expression Pattern Analysis,Transcript Expression Analysis,Transcriptome Profiling,Transcriptomics,mRNA Differential Display,Gene Expression Monitoring,Transcriptome Analysis,Analyses, Gene Expression,Analyses, Transcript Expression,Analyses, Transcriptome,Analysis, Gene Expression,Analysis, Transcript Expression,Analysis, Transcriptome,Differential Display, mRNA,Differential Displays, mRNA,Expression Analyses, Gene,Expression Analysis, Gene,Gene Expression Analyses,Gene Expression Monitorings,Gene Expression Profilings,Monitoring, Gene Expression,Monitorings, Gene Expression,Profiling, Gene Expression,Profiling, Transcriptome,Profilings, Gene Expression,Profilings, Transcriptome,Transcript Expression Analyses,Transcriptome Analyses,Transcriptome Profilings,mRNA Differential Displays