Rotation Testing in Gene Set Enrichment Analysis for Small Direct Comparison Experiments
Rotation Testing in Gene Set Enrichment Analysis for Small Direct Comparison Experiments
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DOI：
10.2202/1544-6115.1418
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发表时间：
2009-01-01
影响因子：
0.9
通讯作者：
Saebo, Solve
中科院分区：
文献类型：
--
作者：
Dorum, Guro;Snipen, Lars;Saebo, Solve
基因集富集分析 (GSEA) 是一种分析基因表达数据的方法，重点关注先验定义的基因集。 GSEA 中通常用于测试基因集富集重要性的排列测试涉及表型向量的排列，并且是针对来自间接比较设计的数据（即未配对数据）而开发的。在一些研究中，代表两种表型的样本是配对的，例如治疗前后从患者身上采集的样本，或者代表两种表型的样本与相同的双通道阵列杂交（直接比较设计）。在本文中，我们将重点关注直接比较实验的数据，但这些方法通常可以应用于配对数据。对于这些类型的数据，可以使用随机重新签名样本的配对数据的标准排列测试。然而，如果样本量非常小（直接比较设计通常会出现这种情况），则排列检验将给出非常不精确的 p 值估计。在这里，我们建议使用旋转检验而不是排列检验来估计 GSEA 中与有限数量样本的直接比较数据的显着性。我们提出的旋转测试通过依赖于数据的旋转而不是排列，使 GSEA 适用于具有少量样本的直接比较数据。旋转测试是排列测试的推广，此外还可用于间接比较数据以及测试 GSEA 框架之外其他类型测试统计量的显着性。
Gene Set Enrichment Analysis (GSEA) is a method for analysing gene expression data with a focus on a priori defined gene sets. The permutation test generally used in GSEA for testing the significance of gene set enrichment involves permutation of a phenotype vector and is developed for data from an indirect comparison design, i.e. unpaired data. In some studies the samples representing two phenotypes are paired, e.g. samples taken from a patient before and after treatment, or if samples representing two phenotypes are hybridised to the same two-channel array (direct comparison design). In this paper we will focus on data from direct comparison experiments, but the methods can be applied to paired data in general. For these types of data, a standard permutation test for paired data that randomly re-signs samples can be used. However, if the sample size is very small, which is often the case for a direct comparison design, a permutation test will give very imprecise estimates of the p-values. Here we propose using a rotation test rather than a permutation test for estimation of significance in GSEA of direct comparison data with a limited number of samples. Our proposed rotation test makes GSEA applicable to direct comparison data with few samples, by depending on rotations of the data instead of permutations. The rotation test is a generalisation of the permutation test, and can in addition be used on indirect comparison data and for testing significance of other types of test statistics outside the GSEA framework.