Jen Chih-Hung, Manfield Iain W, Michalopoulos Ioannis, Pinney John W, Willats William G T, Gilmartin Philip M, Westhead David R
School of Biochemistry and Microbiology, University of Leeds, Leeds, West Yorkshire, LS2 9JT, UK.
Plant J. 2006 Apr;46(2):336-48. doi: 10.1111/j.1365-313X.2006.02681.x.
We present a new WWW-based tool for plant gene analysis, the Arabidopsis Co-Expression Tool (ACT), based on a large Arabidopsis thaliana microarray data set obtained from the Nottingham Arabidopsis Stock Centre. The co-expression analysis tool allows users to identify genes whose expression patterns are correlated across selected experiments or the complete data set. Results are accompanied by estimates of the statistical significance of the correlation relationships, expressed as probability (P) and expectation (E) values. Additionally, highly ranked genes on a correlation list can be examined using the novel clique finder tool to determine the sets of genes most likely to be regulated in a similar manner. In combination, these tools offer three levels of analysis: creation of correlation lists of co-expressed genes, refinement of these lists using two-dimensional scatter plots, and dissection into cliques of co-regulated genes. We illustrate the applications of the software by analysing genes encoding functionally related proteins, as well as pathways involved in plant responses to environmental stimuli. These analyses demonstrate novel biological relationships underlying the observed gene co-expression patterns. To demonstrate the ability of the software to develop testable hypotheses on gene function within a defined biological process we have used the example of cell wall biosynthesis genes. The resource is freely available at http://www.arabidopsis.leeds.ac.uk/ACT/
我们基于从诺丁汉拟南芥种子中心获得的大量拟南芥微阵列数据集,展示了一种新的基于万维网的植物基因分析工具——拟南芥共表达工具(ACT)。该共表达分析工具允许用户识别在选定实验或完整数据集中其表达模式相关的基因。结果还附带了相关关系统计显著性的估计值,以概率(P)和期望值(E)表示。此外,可以使用新颖的团簇查找工具检查相关列表中排名靠前的基因,以确定最有可能以相似方式受到调控的基因集。这些工具结合起来提供了三个分析层次:创建共表达基因的相关列表、使用二维散点图细化这些列表,以及分解为共调控基因的团簇。我们通过分析编码功能相关蛋白质的基因以及植物对环境刺激反应所涉及的途径,来说明该软件的应用。这些分析揭示了观察到的基因共表达模式背后新的生物学关系。为了证明该软件在定义的生物学过程中对基因功能提出可测试假设的能力,我们以细胞壁生物合成基因为例。该资源可在http://www.arabidopsis.leeds.ac.uk/ACT/免费获取。