Futschik Matthias E, Herzel Hanspeter
Institute for Theoretical Biology, Charité, Humboldt-Universität, Invalidenstrasse 43, 10115 Berlin, Germany.
Bioinformatics. 2008 Apr 15;24(8):1063-9. doi: 10.1093/bioinformatics/btn072. Epub 2008 Feb 29.
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.
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.
R scripts are available on request from the corresponding author.
周期性过程在生物体中起着基础性作用。突出的例子是细胞周期和生物钟。微阵列技术使我们能够在全系统水平上筛选完整的转录本集合，以寻找与这些基本周期性过程可能存在的关联。通常，已检测到相当数量的基因呈周期性表达。然而，不同研究中鉴定出的基因之间重叠较少，这对所检测到的周期性表达的可靠性产生了一些质疑。
在本研究中，比较分析表明不同细胞周期研究之间缺乏一致性可能是由于用于确定显著性的背景模型不充分。我们证明背景模型的选择对周期性表达的统计显著性有相当大的影响。为了说明这一点，我们重新分析了两项酵母细胞周期的微阵列研究。我们的评估有力地表明，先前分析的结果可能过于乐观，而使用更合适的背景模型有望得出更现实的结果。
可根据要求向通讯作者索取R脚本。
