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

Bioinformatics. 2008 Apr 15;24(8):1063-9. doi: 10.1093/bioinformatics/btn072. Epub 2008 Feb 29.

Abstract

Motivation: 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 large numbers of genes have been detected as periodically expressed. However, the small overlap between genes identified in different studies has cast some doubts on the reliability of the periodic expression detected.

Results: In this study, comparative analysis suggests that the lacking agreement between different cell-cycle studies might be due to inadequate background models 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.

Availability: R scripts are available on request from the corresponding author.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Artifacts
  • Cell Cycle / physiology*
  • Cell Cycle Proteins / metabolism*
  • Computer Simulation
  • Gene Expression Profiling / methods*
  • Models, Biological*
  • Oligonucleotide Array Sequence Analysis / methods
  • Reproducibility of Results
  • Saccharomyces cerevisiae / cytology*
  • Saccharomyces cerevisiae / metabolism*
  • Saccharomyces cerevisiae Proteins / metabolism*
  • Sensitivity and Specificity

Substances

  • Cell Cycle Proteins
  • Saccharomyces cerevisiae Proteins