Abstract：
Estimating the false discovery rate (FDR) of peptide identifications is a key step in proteomics data analysis, and many methods have been proposed for this purpose. Recently, an entrapment-inspired protocol to validate methods for FDR estimation appeared in articles showcasing new spectral library search tools. That validation approach involves generating incorrect spectral matches by searching spectra from evolutionarily distant organisms (entrapment queries) against the original target search space. Although this approach may appear similar to the solutions using entrapment databases, it represents a distinct conceptual framework whose correctness has not been verified yet. In this viewpoint, we first discussed the background of the entrapment-based validation protocols and then conducted a few simple computational experiments to verify the assumptions behind them. The results reveal that entrapment databases may, in some implementations, be a reasonable choice for validation, while the assumptions underpinning validation protocols based on entrapment queries are likely to be violated in practice. This article also highlights the need for well-designed frameworks for validating FDR estimation methods in proteomics.
摘要：
估计肽鉴定的错误发现率（FDR）是蛋白质组学数据分析的关键步骤。并且已经为此提出了许多方法。最近,用于验证FDR估计方法的诱捕式协议出现在展示新的光谱库搜索工具的文章中.该验证方法涉及通过针对原始目标搜索空间搜索来自进化上遥远的生物体的光谱(诱捕查询)来生成不正确的光谱匹配。虽然这种方法可能看起来类似于使用诱捕数据库的解决方案，它代表了一个独特的概念框架，其正确性尚未得到验证。在这个观点中,我们首先讨论了基于诱捕的验证方案的背景,然后进行了一些简单的计算实验来验证其背后的假设.结果表明，诱捕数据库可能，在一些实现中，是一个合理的验证选择，而支持基于诱捕查询的验证协议的假设在实践中可能会被违反。本文还强调需要精心设计的框架来验证蛋白质组学中的FDR估计方法。
