Using a calibration experiment to assess gene-specific information: full Bayesian and empirical Bayesian models for two-channel microarray data.
BACKGROUND
Microarray studies permit to quantify expression levels on a global scale by measuring transcript abundance of thousands of genes simultaneously. A difficulty when analysing expression measures is how to model variability for the whole set of genes. It is usually unrealistic to assume a common variance for each gene. Several approaches to model gene-specific variances are proposed. We take advantage of calibration experiments, in which the probes hybridized on the two channels come from the same population (self-self experiment). In this case it is possible to estimate the gene-specific variance, to be incorporated in comparative experiments on the same tissue, cellular line or species.


RESULTS
We present two approaches to introduce prior information on gene-specific variability from a calibration experiment: an empirical Bayes model and a full Bayesian hierarchical model. We apply the methods in the analysis of human lipopolysaccharide-stimulated leukocyte experiments.


BACKGROUND
The calculations are implemented in WinBugs. The codes are available on request from the authors.
Blangiardo
Marta
M
Department of Statistics G. Parenti, University of Florence & Biostatistic Unit CSPO, Florence, Italy. m.blangiardo@imperial.ac.uk
Toti
Simona
S
Giusti
Betti
B
Abbate
Rosanna
R
Magi
Alberto
A
Poggi
Filippo
F
Rossi
Luciana
L
Torricelli
Francesca
F
Biggeri
Annibale
A
D000465:Algorithms; D000704:Analysis of Variance; D001499:Bayes Theorem; D002138:Calibration; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D015536:Down-Regulation; D005069:Evaluation Studies as Topic; D005786:Gene Expression Regulation; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007962:Leukocytes / Q000378:metabolism; D007963:Leukocytes, Mononuclear / Q000166:cytology; D008070:Lipopolysaccharides / Q000737:chemistry / Q000378:metabolism; D015233:Models, Statistical; D009693:Nucleic Acid Hybridization; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D012107:Research Design; D012680:Sensitivity and Specificity; D014894:Weights and Measures
D008070:Lipopolysaccharides