Optimizing Reference Gene Set for Inter-Chip Normalization Using Genetic Algorithm

Due to the existence of systematic bias in the measurements, inter-chip normalization is required before integrated data analysis of multiple microarray datasets. Current inter-chip normalization methods rely on some assumptions, which can rarely be verified by experiments, such as the invariant expression level of housekeeping genes or the stability of statistical data distribution. In this paper, we present a highly verifiable inter-chip normalization method using genetic optimization algorithm, which depends only on a small number of housekeeping genes, and therefore facilitates experimental validation without any accuracy lost.