Effect of local background intensities in the normalization of cDNA microarray data with a skewed expression profiles

Abstract

Normalization of the data of cDNA microarray is an obligatory step during microarray experiments due to the relatively frequent non-specific errors. Generally, normalization of microarray data is based on the null hypothesis and variance model. In the Yang's model (Yang et al., 2001), at least two types of noises are included. The one is additive noise and the other is multiplicative noise. Usually, background is considered as one of additive noise to the signal and the variation between the signal pixels is the representative multiplicative noise. In this study, the relation between the signal (spot intensity minus background intensity) and background was observed and the influence of background on normalization as a representative additive factor was investigated. Although the relation has not been considered as a factor affecting the normalization, it could improve the accuracy of microarray data when the normalization was carried out considering signal/background ratio. The background dependent normalization decreased the number of genes whose expression levels were changed significantly and it could make their distribution more consistent through the whole range of signal intensities. In this study, printing pin dependent normalization was also carried out regarding the printing pin as a representative multiplicative noise. It improved the distribution of spots in the Cy3-Cy5 scatter plot, but its effect was slight. These studies suggest that there are some influences of the signals on the local backgrounds and they must be considered for the normalization of cDNA microarray data.