From the ‡Institute of Plant Biology and Biotechnology, University of Muenster, Schlossplatz 8, 48143 Muenster, Germany.
§Max Planck Research Group for RNA Biology, Max Planck Institute for Molecular Biomedicine, Von-Esmarch-Strasse 54, 48149 Muenster, Germany.
Mol Cell Proteomics. 2017 Oct;16(10):1736-1745. doi: 10.1074/mcp.M117.068007. Epub 2017 Jul 20.
Quantitative mass spectrometry (MS) is a key technique in many research areas (1), including proteomics, metabolomics, glycomics, and lipidomics. Because all of the corresponding molecules can be described by chemical formulas, universal quantification tools are highly desirable. Here, we present pyQms, an open-source software for accurate quantification of all types of molecules measurable by MS. pyQms uses isotope pattern matching that offers an accurate quality assessment of all quantifications and the ability to directly incorporate mass spectrometer accuracy. pyQms is, due to its universal design, applicable to every research field, labeling strategy, and acquisition technique. This opens ultimate flexibility for researchers to design experiments employing innovative and hitherto unexplored labeling strategies. Importantly, pyQms performs very well to accurately quantify partially labeled proteomes in large scale and high throughput, the most challenging task for a quantification algorithm.
定量质谱(MS)是许多研究领域(1)的关键技术,包括蛋白质组学、代谢组学、糖组学和脂质组学。由于所有对应的分子都可以用化学式来描述,因此非常需要通用的定量工具。在这里,我们介绍了 pyQms,这是一种用于 MS 可测量的所有类型分子的精确定量的开源软件。pyQms 使用同位素模式匹配,为所有定量提供准确的质量评估,并能够直接纳入质谱仪的准确性。由于其通用的设计,pyQms 适用于每个研究领域、标记策略和采集技术。这为研究人员设计实验提供了终极的灵活性,采用创新的、迄今为止尚未探索过的标记策略。重要的是,pyQms 能够非常好地在大规模和高通量下精确地定量部分标记的蛋白质组,这是定量算法最具挑战性的任务。