For RNA-seq studies, an important task is to identify genes that are differentially expressed between groups. Nevertheless, the identification of differentially expressed (DE) genes from a single study can be challenging as the small number of samples and the high sensitivity of data perturbations. Combining -values from multiple RNA-seq studies can increase the statistical power and the accuracy in detecting DE genes. In this paper, we propose a weight and truncation -value combination test for meta-analyzing RNA-seq studies. We show that with proper weight and truncation parameters, our new test has a higher statistical power over the existing tests, when the genes are weakly expressed in most studies and the sample size is unbalanced. We then present simulations and apply to two real data analysis. Finally, we provide some practical guidance for our new test and some existing -value combination tests.

中文翻译：

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使用自适应权重和截断 p 值组合检验对 RNA-seq 研究进行荟萃分析


对于RNA-seq研究，一项重要任务是识别组间差异表达的基因。然而，由于样本数量少且数据扰动的敏感性高，从单个研究中鉴定差异表达（DE）基因可能具有挑战性。组合多个 RNA-seq 研究的 β 值可以提高检测 DE 基因的统计功效和准确性。在本文中，我们提出了一种用于荟萃分析 RNA-seq 研究的权重和截断值组合测试。我们表明，当大多数研究中基因表达较弱且样本量不平衡时，通过适当的权重和截断参数，我们的新测试比现有测试具有更高的统计功效。然后我们提出模拟并应用于两个实际数据分析。最后，我们为我们的新测试和一些现有的值组合测试提供了一些实用指导。