Inference of a genetic network by a combined approach of cluster analysis and graphical Gaussian modeling

Inference of a genetic network by a combined approach of cluster analysis and graphical Gaussian modeling
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DOI:
10.1093/bioinformatics/18.2.287
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发表时间:
2002-02-01
期刊:
影响因子:
5.8
通讯作者:
Horimoto, K
Horimoto, K
中科院分区:
生物学3区
文献类型:
--
作者:
Toh, H;Horimoto, K

文献摘要

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动机:DNA微阵列技术的最新进展使在不同条件下同时测量数千个基因的表达水平成为可能。通过微阵列分析获得的数据称为表达谱数据。表达谱数据背后的一种重要信息是“遗传网络”,也就是基因之间的调控网络。图形高斯建模(GGM)是一种广泛使用的方法,用于推断或检验多个变量之间的关系。结果:在本研究中,我们提出了一种将聚类分析与GGM相结合的方法,用于从表达谱数据中推断遗传网络。在79种不同条件下测量的2467个酿酒酵母基因的表达谱数据(Eisen等人,Proc.纳特·阿卡德。SCI。美国,95,14 683-14 868,1998)用于本研究。首先,通过聚类分析将2467个基因分为34个类群,作为GGM的前处理。然后,针对每种情况计算每个簇中基因的平均表达水平。对34个簇的平均表达谱数据进行GGM分析,得到偏相关系数矩阵,作为酿酒酵母遗传网络的模型。通过我们的结果与实验研究的累积结果的一致性来检验推断网络的准确性。
Motivation: Recent advances in DNA microarray technologies have made it possible to measure the expression levels of thousands of genes simultaneously under different conditions. The data obtained by microarray analyses are called expression profile data. One type of important information underlying the expression profile data is the 'genetic network,' that is, the regulatory network among genes. Graphical Gaussian Modeling (GGM) is a widely utilized method to infer or test relationships among a plural of variables.Results: In this study, we developed a method combining the cluster analysis with GGM for the inference of the genetic network from the expression profile data. The expression profile data of 2467 Saccharomyces cerevisiae genes measured under 79 different conditions (Eisen et al., Proc. Natl Acad. Sci. USA, 95, 14 683-14 868, 1998) were used for this study. At first, the 2467 genes were classified into 34 clusters by a cluster analysis, as a preprocessing for GGM. Then, the expression levels of the genes in each cluster were averaged for each condition. The averaged expression profile data of 34 clusters were subjected to GGM, and a partial correlation coefficient matrix was obtained as a model of the genetic network of S. cerevisiae. The accuracy of the inferred network was examined by the agreement of our results with the cumulative results of experimental studies.