Prediction of the gene expression measure by means of a GLMM

Microarrays permit to scientists the screening of thousands of genes simultaneously todetermine, for example, whether those genes are active, hyperactive or silent in normal orcancerous tissues. A primary task in microarray analysis is to obtain a good measure of thegene expression that can be used for a so called higher level analysis. Different methodshave been proposed for high density oligonucleotide arrays (see Cope et al. (2004) fora review). Aim of this paper is to obtain a new gene expression measure based on thebackground correction model proposed by Mineo et al. (2006). The proposed method isvalidated by means of a free available data-set called Spike-In133 experiment, where 42genes are spiked in 42 arrays at known concentration from 0 to 512 pico-Molar (pM).