Enhanced Sensitivity and Quantitative Precision for Single Cell Proteomics

单细胞蛋白质组学(SCP)正在迅速兴起，可以对每个细胞的1000个蛋白质进行定量。 仪器和样品制备方面的重大进步使SCP得到更广泛的应用 无障碍。然而，数据采集方面的技术进步并没有与以下方面的进步相匹配 计算工具。基于大量的数据，设计和优化了蛋白质组学算法 蛋白质组学，并且不适合SCP数据。我们的初步研究表明，来自SCP的数据 缺乏许多对当前蛋白质组学算法至关重要的功能。我们将戏剧性地 通过首次创建单细胞蛋白质组来提高单细胞蛋白质组的准确性和覆盖率 专用SCP搜索软件。这将伴随着一项改进SCP多肽的倡议 和蛋白质的量化。这些算法改进将从一个大型语料库中得到通知 收集SCP数据并集中到第一个SCP数据归档中。

Single cell proteomics (SCP) is rapidly emerging and can quantify > 1000 proteins per cell. Significant advances in instrumentation and sample preparation are making SCP more broadly accessible. Yet technical advances in data acquisition have not been paired with advances to computational tools. Algorithms for proteomics were designed and optimized on data from bulk proteomics, and are ill-suited for SCP data. Our preliminary research shows that data from SCP lack many features that are critical for current proteomics algorithms. We will dramatically improve accuracy and coverage of the single cell proteome through creation of the first-ever dedicated SCP search software. This will be coupled with an initiative to improve SCP peptide and protein quantification. These algorithmic improvements will be informed from a large corpus of SCP data, gathered and centralized into the first SCP data archive.