Discovering statistically significant pathways in expression profiling studies
Discovering statistically significant pathways in expression profiling studies
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DOI：
10.1073/pnas.0506577102
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发表时间：
2005-09-20
影响因子：
11.1
通讯作者：
Park, PJ
中科院分区：
文献类型：
--
作者：
Tian, L;Greenberg, SA;Park, PJ
通过分析全基因组表达谱来准确和快速地识别受干扰的途径有助于生物学假说的产生。我们提出了一个统计框架，以确定是否一个特定的一组基因的途径有一个协调的关联与感兴趣的表型。对适当的假设检验程序的几个问题进行了澄清。特别是，它示出的基因的每一组的相关性结构的差异可能会导致一个有偏见的基因集之间的比较，除非应用一个归一化程序。我们提出了两个重要的，但不同的方面的协会每组基因的统计检验。这种方法比目前可用的方法具有更大的统计功效，并且可以发现其他方法无法检测到的统计学显著途径。这种方法适用于涉及糖尿病，炎症性肌病和阿尔茨海默病的数据集，使用我们从各种公共数据库编译的基因集。在炎性肌病的情况下，我们已经正确地确定了已知的细胞毒性T淋巴细胞介导的自身免疫性包涵体肌炎。此外，我们预测了树突状细胞在包涵体肌炎和IFN-α/β反应皮肌炎的存在，这两个都没有以前描述。这些预测随后被免疫组织化学证实。
Accurate and rapid identification of perturbed pathways through the analysis of genome-wide expression profiles facilitates the generation of biological hypotheses. We propose a statistical framework for determining whether a specified group of genes for a pathway has a coordinated association with a phenotype of interest. Several issues on proper hypothesis-testing procedures are clarified. In particular, it is shown that the differences in the correlation structure of each set of genes can lead to a biased comparison among gene sets unless a normalization procedure is applied. We propose statistical tests for two important but different aspects of association for each group of genes. This approach has more statistical power than currently available methods and can result in the discovery of statistically significant pathways that are not detected by other methods. This method is applied to data sets involving diabetes, inflammatory myopathies, and Alzheimer's disease, using gene sets we compiled from various public databases. In the case of inflammatory myopathies, we have correctly identified the known cytotoxic T lymphocyte-mediated autoimmunity in inclusion body myositis. Furthermore, we predicted the presence of dendritic cells in inclusion body myositis and of an IFN-alpha/beta response in dermatomyositis, neither of which was previously described. These predictions have been subsequently corroborated by immunohistochemistry.