Label-free quantification has grown in popularity as a means of obtaining relative abundance measures for proteomics experiments. However, easily accessible and integrated tools to perform label-free quantification have been lacking. We describe StPeter, an implementation of Normalized Spectral Index quantification for wide availability through integration into the widely used Trans-Proteomic Pipeline. This implementation has been specifically designed for reproducibility and ease of use. We demonstrate that StPeter outperforms other state-of-the art packages using a recently reported benchmark data set over the range of false discovery rates relevant to shotgun proteomics results. We also demonstrate that the software is computationally efficient and supports data from a variety of instrument platforms and experimental designs. Results can be viewed within the Trans-Proteomic Pipeline graphical user interfaces and exported in standard formats for downstream statistical analysis. By integrating StPeter into the freely available Trans-Proteomic Pipeline, users can now obtain high-quality label-free quantification of any data set in seconds by adding a single command to the workflow.

中文翻译：

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StPeter：跨蛋白质组学管线实现无缝，无标签定量

作为蛋白质组学实验中获得相对丰度指标的一种手段，无标记定量法已越来越普及。但是，缺乏执行无标签定量的易于访问和集成的工具。我们将介绍StPeter，这是归一化频谱指数量化的一种实现方式，可通过集成到广泛使用的跨蛋白质组学管道中来实现广泛的可用性。此实现已为重现性和易用性专门设计。我们证明，在与shot弹枪蛋白质组学结果相关的错误发现率范围内，StPeter使用最近报告的基准数据集优于其他最新软件包。我们还演示了该软件的计算效率，并支持来自各种仪器平台和实验设计的数据。可以在蛋白质组学流水线图形用户界面中查看结果，并以标准格式导出以进行下游统计分析。通过将StPeter集成到免费的跨蛋白质组学管线中，用户现在只需在工作流程中添加单个命令，即可在几秒钟内获得任何数据集的高质量，无标签定量。