Prediction of the gene expression measure by means of a GLMM

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