Empirical comparison of structure-based pathway methods.
Empirical comparison of structure-based pathway methods.
复制标题
DOI：
10.1093/bib/bbv049
复制
发表时间：
2016-03
影响因子：
9.5
通讯作者：
Elo LL
中科院分区：
文献类型：
--
作者：
Jaakkola MK;Elo LL
人们已经提出了多种方法来根据表达谱来估计通路的活性，然而，关于这些方法的性能还没有足够的信息可用。这使得为通路分析选择合适的工具变得困难。尽管基于简单基因列表的方法仍然是最常用的方法，但也出现了各种考虑途径结构的方法。为了对基于列表和基于结构的方法的性能提供实用的见解，我们在两个不同特征的不同案例研究环境中测试了六种不同的方法来估计途径活动。第一个病例研究背景涉及6个肾细胞癌数据集，病例和对照样本的表达谱差异相对较大。第二个病例研究背景包括四个1型糖尿病数据集，病例样本和对照样本的轮廓彼此更相似。总体而言，即使有相同的输入数据，不同途径工具的结果也有显著差异。在癌症研究中，一种测试方法的结果在不同的数据集上通常是一致的，但不同方法之间的结果不同。在更具挑战性的糖尿病研究中，几乎所有被测试的方法都被检测为有意义的，只有少数几个途径被检测到。
Multiple methods have been proposed to estimate pathway activities from expression profiles, and yet, there is not enough information available about the performance of those methods. This makes selection of a suitable tool for pathway analysis difficult. Although methods based on simple gene lists have remained the most common approach, various methods that also consider pathway structure have emerged. To provide practical insight about the performance of both list-based and structure-based methods, we tested six different approaches to estimate pathway activities in two different case study settings of different characteristics. The first case study setting involved six renal cell cancer data sets, and the differences between expression profiles of case and control samples were relatively big. The second case study setting involved four type 1 diabetes data sets, and the profiles of case and control samples were more similar to each other. In general, there were marked differences in the outcomes of the different pathway tools even with the same input data. In the cancer studies, the results of a tested method were typically consistent across the different data sets, yet different between the methods. In the more challenging diabetes studies, almost all the tested methods detected as significant only few pathways if any.