Multiple hypothesis testing in radiobiological omics study / 中华放射医学与防护杂志

With the development of high-throughput sequencing technology, the high-dimensional massive data obtained in omics study puts forward new requirements for statistical analysis. In this case, the traditional theory of single hypothesis testing is no longer applicable, and the issue of multiple hypothesis testing has received increasing attention. This paper introduced three commonly used error measures in multiple testing-family-wise error rate (FWER), false discovery rate (FDR), and positive false discovery rate (pFDR), and the control process in radiobiological omics data analysis, in order to provide a reference for statistical analysis of radiobiological data.