Two-part permutation tests for DNA methylation and microarray data -: art. no. 35
Two-part permutation tests for DNA methylation and microarray data -: art. no. 35
复制标题
DOI：
10.1186/1471-2105-6-35
复制
发表时间：
2005-02-22
影响因子：
3
通讯作者：
Jöckel, KH
中科院分区：
文献类型：
--
作者：
Neuhäuser, M;Boes, T;Jöckel, KH
背景：微阵列实验的一个重要应用是鉴定差异表达的基因。通常，在进行统计学检验之前，将小的和阴性的表达水平剪切为等于任意选择的截止值。然后，有两种类型的数据：截断值和原始观测值。截断值不仅仅是可能值连续体上的另一个点，因此，在两部分模型中结合联合收割机两个统计检验而不是使用标准统计方法是合适的。在研究DNA甲基化数据时也会出现类似的情况。在这种情况下，存在空值（不可检测的甲基化）和观察到的正值。对于这些数据，我们提出了一个两部分排列test.Results：建议的排列测试导致较小的p值相比，原来的两部分测试。我们在DNA甲基化数据和微阵列数据中都发现了这一点。通过模拟研究，我们证实了这一结果，并可以表明，两部分排列测试，平均而言，更强大。新的测试也减少了，没有任何损失的权力，一个标准的测试时，有没有空值或截断values.Conclusion：两部分排列测试可以用于常规分析，因为它减少了标准测试时，只有正值。新检验的进一步优点是，它开辟了使用其他检验统计量来构造两部分检验的可能性，并且它避免了使用任何渐近分布。后者的优点是特别重要的微阵列的分析，因为样本量通常很小。
Background: One important application of microarray experiments is to identify differentially expressed genes. Often, small and negative expression levels were clipped-off to be equal to an arbitrarily chosen cutoff value before a statistical test is carried out. Then, there are two types of data: truncated values and original observations. The truncated values are not just another point on the continuum of possible values and, therefore, it is appropriate to combine two statistical tests in a two-part model rather than using standard statistical methods. A similar situation occurs when DNA methylation data are investigated. In that case, there are null values (undetectable methylation) and observed positive values. For these data, we propose a two-part permutation test.Results: The proposed permutation test leads to smaller p-values in comparison to the original two-part test. We found this for both DNA methylation data and microarray data. With a simulation study we confirmed this result and could show that the two-part permutation test is, on average, more powerful. The new test also reduces, without any loss of power, to a standard test when there are no null or truncated values.Conclusion: The two-part permutation test can be used in routine analyses since it reduces to a standard test when there are positive values only. Further advantages of the new test are that it opens the possibility to use other test statistics to construct the two-part test and that it avoids the use of any asymptotic distribution. The latter advantage is particularly important for the analysis of microarrays since sample sizes are usually small.