用主成分分析探索基因表达模式

Principal Component Analysis for Exploring Gene Expression Patterns

以时间点(阵列)为变量,对酵母时间表达序列进行主成分分析,提取出三个主成分:第一主成分代表整个酵母细胞周期中平稳的基因表达状态,第二主成分代表酵母细胞周期中lateG1期和M期差异的基因表达状态,第三主成分表示的是earlyG1期和S/G2期差异的基因表达状态。由第二、和第三主成分揭示出基因表达谱中四个周期性基因表达模式:分别对应lateG1期、M期、earlyG1期和S/G2期,而且发现了一批表达水平呈周期性变化的基因,为进一步研究基因周期性表达和基因调控网络提供有价值的指导。

When projecting microarray data of yeast time series into principal component space based on timepoints （arrays）, we can not only ascribe biologically meaningful explanations to the first few principal components, but also discover sensible gene expression patterns and the according genes with periodic fluctuation ; this helps the subsequent research of gene periodic expression and gene regulatory network.