Ficarro Scott B, Alexander William M, Marto Jarrod A
Department of Cancer Biology and Blais Proteomics Center, Dana-Farber Cancer Institute, 450 Brookline Avenue, Boston, MA 02115, USA.
Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02215, USA.
Proteomes. 2017 Aug 1;5(3):20. doi: 10.3390/proteomes5030020.
Although not yet truly 'comprehensive', modern mass spectrometry-based experiments can generate quantitative data for a meaningful fraction of the human proteome. Importantly for large-scale protein expression analysis, robust data pipelines are in place for identification of un-modified peptide sequences and aggregation of these data to protein-level quantification. However, interoperable software tools that enable scientists to computationally explore and document novel hypotheses for peptide sequence, modification status, or fragmentation behavior are not well-developed. Here, we introduce mzStudio, an open-source Python module built on our multiplierz project. This desktop application provides a highly-interactive graphical user interface (GUI) through which scientists can examine and annotate spectral features, re-search existing PSMs to test different modifications or new spectral matching algorithms, share results with colleagues, integrate other domain-specific software tools, and finally create publication-quality graphics. mzStudio leverages our common application programming interface (mzAPI) for access to native data files from multiple instrument platforms, including ion trap, quadrupole time-of-flight, Orbitrap, matrix-assisted laser desorption ionization, and triple quadrupole mass spectrometers and is compatible with several popular search engines including Mascot, Proteome Discoverer, X!Tandem, and Comet. The mzStudio toolkit enables researchers to create a digital provenance of data analytics and other evidence that support specific peptide sequence assignments.
尽管现代基于质谱的实验尚未真正做到“全面”，但能够为相当一部分人类蛋白质组生成定量数据。对于大规模蛋白质表达分析而言重要的是，目前已有强大的数据流程用于鉴定未修饰的肽序列，并将这些数据汇总为蛋白质水平的定量分析。然而，能让科学家通过计算探索并记录有关肽序列、修饰状态或碎片化行为的新假设的可互操作软件工具却并未得到充分发展。在此，我们推出mzStudio，这是一个基于我们的multiplierz项目构建的开源Python模块。这个桌面应用程序提供了一个高度交互式的图形用户界面（GUI），科学家可以通过它检查和注释光谱特征、重新搜索现有肽段谱匹配结果（PSM）以测试不同的修饰或新的光谱匹配算法、与同事分享结果、整合其他特定领域的软件工具，最后创建可用于发表的高质量图形。mzStudio利用我们的通用应用程序编程接口（mzAPI）来访问来自多个仪器平台的原生数据文件，包括离子阱、四极杆飞行时间、轨道阱、基质辅助激光解吸电离和三重四极杆质谱仪，并且与包括 Mascot、Proteome Discoverer、X!Tandem 和 Comet 在内的几种流行搜索引擎兼容。mzStudio工具包使研究人员能够创建数据分析和其他支持特定肽序列分配的证据的数字来源。
