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Mixed-Data Acquisition: Next-Generation Quantitative Proteomics Data Acquisition

机译:混合数据采集:下一代定量蛋白质组学数据采集

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We present the Mixed-Data Acquisition (MDA) strategy for mass spectrometry data acquisition. MDA combines Data-Dependent Acquisition (DDA) and Data-Independent Acquisition (DIA) in the same run, thus doing away with the requirements for separate DDA spectral libraries. MDA is a natural result from advances in mass spectrometry, such as high scan rates and multiple analyzers, and is tailored toward exploiting these features. We demonstrate MDA's effectiveness on a yeast proteome analysis by overcoming a common bottleneck for XIC-based label-free quantitation; namely, the coelution of precursors when m/z values cannot be distinguished. We anticipate that MDA will become the next mainstream data generation approach for proteomics. MDA can also serve as an orthogonal validation approach for DDA experiments. Specialized software for MDA data analysis is made available on the projects website.
机译:我们介绍了用于质谱数据采集的混合数据采集(MDA)策略。 MDA将数据相关的采集(DDA)和数据无关的获取(DIA)相结合,从而消除了单独的DDA谱库的要求。 MDA是来自质谱法的进步的自然导致,例如高扫描速率和多个分析仪,并针对利用这些特征而定制。 我们通过克服基于XIC的无标签定量的共同瓶颈来证明MDA对酵母蛋白质组分析的有效性; 即,当不能区分m / z值时,前体的芯利。 我们预计MDA将成为蛋白质组学的下一个主流数据生成方法。 MDA还可以作为DDA实验的正交验证方法。 MDA数据分析的专业软件在项目网站上提供。

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