Pathway and gene-set activation measurement from mRNA expression data: the tissue distribution of human pathways
Pathway and gene-set activation measurement from mRNA expression data: the tissue distribution of human pathways
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DOI：
10.1186/gb-2006-7-10-r93
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发表时间：
2006-01-01
期刊：
影响因子：
12.3
通讯作者：
Johnson, Jason M.
中科院分区：
文献类型：
--
作者：
Levine, David M.;Haynor, David R.;Johnson, Jason M.
背景资料：基因或蛋白质表达改变的列表的解释是微阵列和蛋白质组学研究的一个关键和耗时的部分，但相对较少的关注已经支付给从这些输出列表中提取生物学意义的方法。一种有效的方法是检查预定义的生物途径和基因组的表达，例如代谢和信号传导途径以及大分子复合物。虽然已经提出了许多方法来测量通路表达，多个方法在多个独立的datasets.Results的性能进行了系统的分析，以前还没有reported.Results：五种不同的措施的通路表达进行了比较，在9个公开的mRNA表达数据集的分析。度量的相对灵敏度在数据集之间变化很大，并且针对每个数据集识别的生物途径也取决于途径激活度量的选择。此外，我们表明，在分析之前去除不相干的途径可以提高特异性。最后，我们创建并分析了一个公共地图的途径表达在人体组织中的基因集分析的一个大纲要的人类expression data.Conclusion：我们表明，在微阵列实验中显着扰动的检测灵敏度和身份的途径是高度依赖于所使用的分析方法和如何处理不连贯的途径。因此，分析师应考虑使用多种方法来测试其生物学解释的稳健性。我们还提供了人类基因通路的组织分布的全面图片和人类通路表达数据的有用的公共档案。
Background: Interpretation of lists of genes or proteins with altered expression is a critical and time-consuming part of microarray and proteomics research, but relatively little attention has been paid to methods for extracting biological meaning from these output lists. One powerful approach is to examine the expression of predefined biological pathways and gene sets, such as metabolic and signaling pathways and macromolecular complexes. Although many methods for measuring pathway expression have been proposed, a systematic analysis of the performance of multiple methods over multiple independent data sets has not previously been reported.Results: Five different measures of pathway expression were compared in an analysis of nine publicly available mRNA expression data sets. The relative sensitivity of the metrics varied greatly across data sets, and the biological pathways identified for each data set are also dependent on the choice of pathway activation metric. In addition, we show that removing incoherent pathways prior to analysis improves specificity. Finally, we create and analyze a public map of pathway expression in human tissues by gene-set analysis of a large compendium of human expression data.Conclusion: We show that both the detection sensitivity and identity of pathways significantly perturbed in a microarray experiment are highly dependent on the analysis methods used and how incoherent pathways are treated. Analysts should thus consider using multiple approaches to test the robustness of their biological interpretations. We also provide a comprehensive picture of the tissue distribution of human gene pathways and a useful public archive of human pathway expression data.