ProGenTomics, Laboratory of Pharmaceutical Biotechnology, Ghent University, 9000, Ghent, Belgium.
VIB-UGent Center for Medical Biotechnology, 9000, Ghent, Belgium.
Proteomics. 2020 Feb;20(3-4):e1900306. doi: 10.1002/pmic.201900306. Epub 2020 Feb 5.
Data-independent acquisition (DIA) generates comprehensive yet complex mass spectrometric data, which imposes the use of data-dependent acquisition (DDA) libraries for deep peptide-centric detection. Here, it is shown that DIA can be redeemed from this dependency by combining predicted fragment intensities and retention times with narrow window DIA. This eliminates variation in library building and omits stochastic sampling, finally making the DIA workflow fully deterministic. Especially for clinical proteomics, this has the potential to facilitate inter-laboratory comparison.
数据非依赖性采集（DIA）生成全面但复杂的质谱数据，这就需要使用数据依赖性采集（DDA）库进行深度的肽-centric 检测。在这里，通过将预测的片段强度和保留时间与窄窗口 DIA 相结合，可以从这种依赖性中赎回 DIA。这消除了库构建中的变化，省略了随机采样，最终使 DIA 工作流程完全确定。特别是对于临床蛋白质组学，这有可能促进实验室间的比较。
