Quantitative set analysis for gene expression: a method to quantify gene set differential expression including gene-gene correlations.
Quantitative set analysis for gene expression: a method to quantify gene set differential expression including gene-gene correlations.
复制标题
DOI：
10.1093/nar/gkt660
复制
发表时间：
2013-10
影响因子：
14.9
通讯作者：
Kleinstein SH
中科院分区：
文献类型：
--
作者：
Yaari G;Bolen CR;Thakar J;Kleinstein SH
基因集的富集分析是一种流行的方法，它提供了全基因组表达数据的功能解释。现有的测试受到基因间相关性的影响，导致高I型错误。最广泛使用的测试，基因集富集分析，依赖于计算密集型排列的样本标签，以产生一个空分布，保持基因-基因的相关性。最近的一种方法CAMERA试图通过直接从数据中估计方差膨胀因子来校正这些相关性。尽管这些方法产生用于检测基因集活性的P值，但它们不能产生置信区间或允许事后比较。我们已经开发了一个新的计算框架，基因表达的定量集分析（QuSAGE）。QuSAGE解释了基因间的相关性，改进了方差膨胀因子的估计，并且它不是用P值来评估与零假设的偏差，而是用完整的概率密度函数来量化基因集的活性。从这个概率密度函数中，可以提取P值和置信区间，并在保持统计可追溯性的同时进行事后分析。与基因集富集分析和CAMERA相比，QuSAGE在描述干扰素治疗（慢性丙型肝炎病毒患者）和甲型流感病毒感染应答的真实的数据上显示出更好的灵敏度和特异性。QuSAGE是一个R软件包，其中包括该方法的核心函数以及绘制和可视化结果的函数。
Enrichment analysis of gene sets is a popular approach that provides a functional interpretation of genome-wide expression data. Existing tests are affected by inter-gene correlations, resulting in a high Type I error. The most widely used test, Gene Set Enrichment Analysis, relies on computationally intensive permutations of sample labels to generate a null distribution that preserves gene–gene correlations. A more recent approach, CAMERA, attempts to correct for these correlations by estimating a variance inflation factor directly from the data. Although these methods generate P-values for detecting gene set activity, they are unable to produce confidence intervals or allow for post hoc comparisons. We have developed a new computational framework for Quantitative Set Analysis of Gene Expression (QuSAGE). QuSAGE accounts for inter-gene correlations, improves the estimation of the variance inflation factor and, rather than evaluating the deviation from a null hypothesis with a P-value, it quantifies gene-set activity with a complete probability density function. From this probability density function, P-values and confidence intervals can be extracted and post hoc analysis can be carried out while maintaining statistical traceability. Compared with Gene Set Enrichment Analysis and CAMERA, QuSAGE exhibits better sensitivity and specificity on real data profiling the response to interferon therapy (in chronic Hepatitis C virus patients) and Influenza A virus infection. QuSAGE is available as an R package, which includes the core functions for the method as well as functions to plot and visualize the results.