6533b835fe1ef96bd129fa21

RESEARCH PRODUCT

Prediction of the gene expression measure by means of a GLMM

subject

description

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).