Are we overestimating the number of cell-cycling genes? The impact of background models for time series data

Abstract

Periodic processes play fundamental roles in organisms. Prominent examples are the cell cycle and the circadian clock. Microarray array technology has enabled us to screen complete sets of transcripts for possible association with such fundamental periodic processes on a system-wide level. Frequently, quite a large number of genes has been detected as periodically expressed. However, the small overlap of identified genes between different studies has shaded considerable doubts about the reliability of the detected periodic expression. In this study, we show that a major reason for the lacking agreement is the use of an inadequate background model for the determination of significance. We demonstrate that the choice of background model has considerable impact on the statistical significance of periodic expression. For illustration, we reanalyzed two microarray studies of the yeast cell cycle. Our evaluation strongly indicates that the results of previous analyses might have been overoptimistic and that the use of more suitable background model promises to give more realistic results.