Wallmann Georg, Leduc Andrew, Slavov Nikolai
Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single Cell Proteomics Center, Northeastern University, Boston, MA 02115, USA.
Parallel Squared Technology Institute, Watertown, MA 02472, USA.
bioRxiv. 2023 Sep 3:2023.02.02.526809. doi: 10.1101/2023.02.02.526809.
Mass spectrometry (MS) enables specific and accurate quantification of proteins with ever increasing throughput and sensitivity. Maximizing this potential of MS requires optimizing data acquisition parameters and performing efficient quality control for large datasets. To facilitate these objectives for data independent acquisition (DIA), we developed a second version of our framework for data-driven optimization of mass spectrometry methods (DO-MS). The DO-MS app v2.0 ( do-ms.slavovlab.net ) allows to optimize and evaluate results from both label free and multiplexed DIA (plexDIA) and supports optimizations particularly relevant for single-cell proteomics. We demonstrate multiple use cases, including optimization of duty cycle methods, peptide separation, number of survey scans per duty cycle, and quality control of single-cell plexDIA data. DO-MS allows for interactive data display and generation of extensive reports, including publication quality figures, that can be easily shared. The source code is available at: github.com/SlavovLab/DO-MS .
质谱分析（MS）能够以不断提高的通量和灵敏度对蛋白质进行特异性和准确的定量分析。要充分发挥质谱分析的这一潜力，需要优化数据采集参数，并对大型数据集进行有效的质量控制。为了实现数据非依赖采集（DIA）的这些目标，我们开发了用于质谱分析方法数据驱动优化（DO-MS）框架的第二个版本。DO-MS应用程序v2.0（do-ms.slavovlab.net）可优化和评估无标记和多重DIA（plexDIA）的结果，并支持与单细胞蛋白质组学特别相关的优化。我们展示了多个用例，包括占空比方法的优化、肽段分离、每个占空比的全扫描次数以及单细胞plexDIA数据的质量控制。DO-MS允许交互式数据显示并生成包括可轻松共享的高质量图表在内的详细报告。源代码可在以下网址获取：github.com/SlavovLab/DO-MS 。
