Analysis of Gene Sets Based on the Underlying Regulatory Network
Analysis of Gene Sets Based on the Underlying Regulatory Network
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DOI：
10.1089/cmb.2008.0081
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发表时间：
2009-03-01
影响因子：
1.7
通讯作者：
Michailidis, George
中科院分区：
文献类型：
--
作者：
Shojaie, Ali;Michailidis, George
网络通常被用来表示基因和蛋白质之间的相互作用。众所周知，这些相互作用在重要的细胞功能中发挥着重要作用，应该包括在差异表达基因的分析中。基因集合分析方法利用外部生物信息，分析先验定义的基因集合。这些方法可以潜在地保持基因之间的相关性；然而，它们不直接结合关于基因网络的信息。本文提出了一种直接结合网络信息的隐变量模型。然后，我们使用混合线性模型理论来给出子网络重要性测试问题的一般推理框架。介绍了几种可能的测试程序，并提出了一种基于网络的方法来测试基因表达水平的变化以及网络结构。该方法的性能与使用两种模拟研究的基因集分析方法以及酵母中半乳糖利用途径相关基因的真实数据进行了比较。
Networks are often used to represent the interactions among genes and proteins. These interactions are known to play an important role in vital cell functions and should be included in the analysis of genes that are differentially expressed. Methods of gene set analysis take advantage of external biological information and analyze a priori defined sets of genes. These methods can potentially preserve the correlation among genes; however, they do not directly incorporate the information about the gene network. In this paper, we propose a latent variable model that directly incorporates the network information. We then use the theory of mixed linear models to present a general inference framework for the problem of testing the significance of subnetworks. Several possible test procedures are introduced and a network based method for testing the changes in expression levels of genes as well as the structure of the network is presented. The performance of the proposed method is compared with methods of gene set analysis using both simulation studies, as well as real data on genes related to the galactose utilization pathway in yeast.