We derive the additive-multiplicative error model for microarray intensities, and describe two applications. For the detection of differentially expressed genes, we obtain a statistic whose variance is approximately independent of the mean intensity. For the post hoc calibration (normalization) of data with respect to experimental factors, we describe a method for parameter estimation.
Microarrays | Statistical Models
Huber, Wolfgang; von Heydebreck, Anja; and Vingron, Martin, "Error models for microarray intensities" (March 2004). Bioconductor Project Working Papers. Working Paper 6.
The paper was submitted to the Encyclopedia of Genomics, Proteomics and Bioinformatics, edited by Michael Dunn, Lynn Jorde, Peter Little and Shankar Subramaniam, to be published by John Wiley & Sons Ltd.