Du Junli, Yuan Zhifa, Ma Ziwei, Song Jiuzhou, Xie Xiaoli, Chen Yulin
College of Sciences, Northwest A&F University, Yangling, 712100, P. R. China.
Mol Biosyst. 2014 Jul 29;10(9):2441-7. doi: 10.1039/c4mb00287c.
The dynamic impact approach (DIA) represents an alternative to overrepresentation analysis (ORA) for functional analysis of time-course experiments or those involving multiple treatments. The DIA can be used to estimate the biological impact of the differentially expressed genes (DEGs) associated with particular biological functions, for example, as represented by the Kyoto encyclopedia of genes and genomes (KEGG) annotations. However, the DIA does not take into account the correlated dependence structure of the KEGG pathway hierarchy. We have developed herein a path analysis model (KEGG-PATH) to subdivide the total effect of each KEGG pathway into the direct effect and indirect effect by taking into account not only each KEGG pathway itself, but also the correlation with its related pathways. In addition, this work also attempts to preliminarily estimate the impact direction of each KEGG pathway by a gradient analysis method from principal component analysis (PCA). As a result, the advantage of the KEGG-PATH model is demonstrated through the functional analysis of the bovine mammary transcriptome during lactation.
动态影响方法（DIA）是一种用于时程实验或涉及多种处理的实验功能分析的替代方法，可替代过表达分析（ORA）。DIA可用于估计与特定生物学功能相关的差异表达基因（DEG）的生物学影响，例如，由京都基因与基因组百科全书（KEGG）注释所代表的功能。然而，DIA没有考虑KEGG通路层次结构的相关依赖结构。我们在此开发了一种路径分析模型（KEGG-PATH），通过不仅考虑每个KEGG通路本身，还考虑其与相关通路的相关性，将每个KEGG通路的总效应细分为直接效应和间接效应。此外，这项工作还尝试通过主成分分析（PCA）的梯度分析方法初步估计每个KEGG通路的影响方向。结果，通过对奶牛泌乳期乳腺转录组的功能分析证明了KEGG-PATH模型的优势。
