To achieve accurate assignment of peptide sequences to observed fragmentation spectra, a shotgun proteomics database search tool must make good use of the very high-resolution information produced by state-of-the-art mass spectrometers. However, making use of this information while also ensuring that the search engine’s scores are well calibrated, that is, that the score assigned to one spectrum can be meaningfully compared to the score assigned to a different spectrum, has proven to be challenging. Here we describe a database search score function, the “residue evidence” (res-ev) score, that achieves both of these goals simultaneously. We also demonstrate how to combine calibrated res-ev scores with calibrated XCorr scores to produce a “combined p value” score function. We provide a benchmark consisting of four mass spectrometry data sets, which we use to compare the combined p value to the score functions used by several existing search engines. Our results suggest that the combined p value achieves state-of-the-art performance, generally outperforming MS Amanda and Morpheus and performing comparably to MS-GF+. The res-ev and combined p-value score functions are freely available as part of the Tide search engine in the Crux mass spectrometry toolkit (http://crux.ms).

中文翻译：

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结合高分辨率和精确校准来提高统计能力：高分辨率MS2数据的校准得分函数

为了准确地将肽序列分配给观察到的碎片光谱，a弹枪蛋白质组学数据库搜索工具必须充分利用最新质谱仪产生的高分辨率信息。但是，在确保搜索引擎的分数得到良好校准的同时利用这一信息，也就是将分配给一个频谱的分数与分配给不同频谱的分数进行有意义的比较已经证明是具有挑战性的。在这里，我们描述了一个数据库搜索评分功能，即“残留证据”（res-ev）评分，该功能可以同时实现这两个目标。我们还演示了如何将校准的res-ev得分与校准的XCorr得分结合起来以产生“合并的p值”得分功能。我们提供了一个由四个质谱数据集组成的基准，用于比较组合的p值与几个现有搜索引擎使用的得分函数。我们的结果表明，组合的p值达到了最先进的性能，通常优于MS Amanda和Morpheus，并且性能与MS-GF +相当。res-ev和组合的p值得分函数可作为Crux质谱工具包（http://crux.ms）中的Tide搜索引擎的一部分免费获得。