Statistical Analysis of Microarray Data: Identification and Classification of Yeast Cell Cycle Genes

Abstract

We are proposing two methods, based on regression approach and estimation—Cmaximization technique, for an in-depth statistical analysis of microarray profiles. The cell cycle-regulated genes were identified and classified basing on statistical analysis of two characteristics—the cell cycle period and the time point of maximal gene expression. Application of the methods proposed to experimental data of Spellman et al. (1998) and Cho et al. (1998) allowed us to find 1628 genes involved in the yeast cell cycle and 171 genes associated with the cell cycle. Thus, we succeeded in increasing the number of genes identified as regulated during the cell cycle more than twofold compared with the analogous data published so far. We also demonstrated that various techniques for synchronizing cell cultures might influence specific features of the cell cycle, in particular, change essentially the activation periodicity of certain genes. In this statistical analysis, an increased attention was paid to a high robustness and reliability of the results obtained, which were controlled using variance characteristics.