MS-based de novo peptide sequencing has been improved remarkably with significant development of mass spectrometry and computational approaches, but still lacks quality control methods. Here we proposed a novel algorithm pSite to evaluate the confidence of each amino acid rather than the full-length peptides obtained by de novo peptide sequencing. A semi-supervised learning approach was used to discriminate correct amino acids from random ones and then an expectation-maximization algorithm was used to adaptively control the false amino-acid rate (FAR). On three test data sets, pSite recalled 86% more amino acids on average than PEAKS at the FAR of 5%. pSite also performed superiorly on the modification site localization problem, which is essentially a special case of amino acid confidence evaluation. On three phosphopeptide data sets, at the false localization rate of 1%, the average recall of pSite was 91% while those of Ascore and phosphoRS were 64% and 63%, respectively. pSite covered 98% of Ascore and phosphoRS results and contributed 21% more phosphorylation sites. Further analyses show that the use of distinct fragmentation features in high-resolution MS/MS spectra, such as neutral loss ions, played an important role in improving the precision of pSite. In summary, the effective and universal model together with the extensive use of spectral information makes pSite an excellent quality control tool for both de novo peptide sequencing and modification site localization.

中文翻译：

---

pSite：用于从头肽测序和修饰位点定位的质量控制的氨基酸置信度评估

随着质谱和计算方法的显着发展，基于质谱的从头肽测序已得到显着改善，但仍缺乏质量控制方法。在这里，我们提出了一种新颖的算法pSite来评估每个氨基酸的可信度，而不是通过从头测序获得的全长肽的可信度。使用半监督学习方法将正确的氨基酸与随机的氨基酸区分开，然后使用期望最大化算法自适应地控制假氨基酸率（FAR）。在三个测试数据集上，pSite在5％的FAR时召回的氨基酸平均比PEAKS多86％。pSite在修饰位点定位问题上也表现出色，这在本质上是氨基酸置信度评估的特例。在三个磷酸肽数据集上，在错误定位率为1％的情况下，pSite的平均召回率为91％，而Ascore和phosphorRS的平均召回率分别为64％和63％。pSite覆盖了98％的Ascore和phosphorRS结果，并​​贡献了21％的磷酸化位点。进一步的分析表明，在高分辨率MS / MS光谱中使用独特的碎片化特征（例如中性丢失离子）在提高pSite的精度中起着重要作用。总之，有效且通用的模型以及广泛使用的光谱信息使pSite成为了从头肽测序和修饰位点定位的出色质量控制工具。pSite覆盖了98％的Ascore和phosphorRS结果，并​​贡献了21％的磷酸化位点。进一步的分析表明，在高分辨率MS / MS光谱中使用独特的碎片化特征（例如中性丢失离子）在提高pSite的精度中起着重要作用。总之，有效且通用的模型以及广泛使用的光谱信息使pSite成为了从头肽测序和修饰位点定位的出色质量控制工具。pSite覆盖了98％的Ascore和phosphorRS结果，并​​贡献了21％的磷酸化位点。进一步的分析表明，在高分辨率MS / MS光谱中使用独特的碎片化特征（例如中性丢失离子）在提高pSite的精度中起着重要作用。总之，有效且通用的模型以及广泛使用的光谱信息使pSite成为了从头肽测序和修饰位点定位的出色质量控制工具。