论文标题
错误的发现率计算：插图和修改
False Discovery Rate Computation: Illustrations and Modifications
论文作者
论文摘要
错误的发现率（FDR）是统计推断的重要组成部分，代表了观察到的结果倾向的倾向。 FDR估计应伴随观察到的结果，以帮助用户上下文化发现的相关性和潜在影响。本文介绍了一个新的用户友好的R软件包，用于计算FDR和调整FDR控制的P值。这些工具尊重调整后的P值与特定发现的估计的FDR之间的关键差异，这些发现有时在数值上是相同的，但在实践中通常会混淆。提出和评估了新的增强方法，用于估计发现的无效比例（FDR估计程序的重要部分）。该软件包很广，包括用于FDR估计和FDR控制的各种方法，并包括绘制功能以简化结果。通过广泛的插图，我们强烈鼓励更广泛地报告发现发现的发现率。
False discovery rates (FDR) are an essential component of statistical inference, representing the propensity for an observed result to be mistaken. FDR estimates should accompany observed results to help the user contextualize the relevance and potential impact of findings. This paper introduces a new user-friendly R package for computing FDRs and adjusting p-values for FDR control. These tools respect the critical difference between the adjusted p-value and the estimated FDR for a particular finding, which are sometimes numerically identical but are often confused in practice. Newly augmented methods for estimating the null proportion of findings - an important part of the FDR estimation procedure - are proposed and evaluated. The package is broad, encompassing a variety of methods for FDR estimation and FDR control, and includes plotting functions for easy display of results. Through extensive illustrations, we strongly encourage wider reporting of false discovery rates for observed findings.
