Combining High-Resolution and Exact Calibration To Boost Statistical Power: A Well-Calibrated Score Function for High-Resolution MS2 Data

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).为了实现将肽序列准确匹配至观测到的碎裂谱，鸟枪法蛋白质组学数据库搜索工具必须充分利用当前最先进质谱仪所产生的超高分辨信息。然而，在利用此类信息的同时，确保搜索引擎的得分得到良好校准——即能够对不同谱图所对应的得分进行有意义的比较——已被证明极具挑战性。本文描述了一种数据库搜索得分函数——「残基证据（residue evidence, res-ev）」得分，其可同时达成上述两大目标。我们还演示了如何将校准后的res-ev得分与校准后的XCorr得分相结合，以构建「组合p值」得分函数。我们提供了一套由四组质谱数据集组成的基准测试集，用于将组合p值与多款现有搜索引擎所采用的得分函数进行对比。实验结果表明，组合p值达到了当前顶尖水准，整体性能优于MS Amanda与Morpheus，且与MS-GF+不相上下。res-ev得分与组合p值得分函数已作为Crux质谱工具包（http://crux.ms）中Tide搜索引擎的组成部分免费开放使用。