Lu Xin, Zhang Wen, Qin Zhaohui S, Kwast Kurt E, Liu Jun S
Department of Statistics, Harvard University, Cambridge, MA 02138, USA.
Nucleic Acids Res. 2004 Jan 22;32(2):447-55. doi: 10.1093/nar/gkh205. Print 2004.
We propose a periodic-normal mixture (PNM) model to fit transcription profiles of periodically expressed (PE) genes in cell cycle microarray experiments. The model leads to a principled statistical estimation procedure that produces more accurate estimates of the mean cell cycle length and the gene expression periodicity than existing heuristic approaches. A central component of the proposed procedure is the resynchronization of the observed transcription profile of each PE gene according to the PNM with estimated periodicity parameters. By using a two-component mixture-Beta model to approximate the PNM fitting residuals, we employ an empirical Bayes method to detect PE genes. We estimate that about one-third of the genes in the genome of Saccharomyces cerevisiae are likely to be transcribed periodically, and identify 822 genes whose posterior probabilities of being PE are greater than 0.95. Among these 822 genes, 540 are also in the list of 800 genes detected by Spellman. Gene ontology annotation analysis shows that many of the 822 genes were involved in important cell cycle-related processes, functions and components. When matching the 822 resynchronized expression profiles of three independent experiments, little phase shifts were observed, indicating that the three synchronization methods might have brought cells to the same phase at the time of release.
我们提出了一种周期-正态混合（PNM）模型，用于拟合细胞周期微阵列实验中周期性表达（PE）基因的转录谱。该模型引出了一种有原则的统计估计程序，与现有的启发式方法相比，它能更准确地估计平均细胞周期长度和基因表达周期性。所提出程序的一个核心组成部分是根据具有估计周期性参数的PNM对每个PE基因的观察到的转录谱进行重新同步。通过使用双组分混合-贝塔模型来近似PNM拟合残差，我们采用经验贝叶斯方法来检测PE基因。我们估计酿酒酵母基因组中约三分之一的基因可能会周期性转录，并鉴定出822个其为PE的后验概率大于0.95的基因。在这822个基因中，有540个也在Spellman检测到的800个基因列表中。基因本体注释分析表明，这822个基因中的许多都参与了重要的细胞周期相关过程、功能和组分。当匹配三个独立实验的822个重新同步的表达谱时，观察到的相位偏移很小，这表明这三种同步方法可能在释放时将细胞带到了相同的相位。
