MSqRob Takes the Missing Hurdle: Uniting Intensity- and Count-Based Proteomics
MSqRob Takes the Missing Hurdle: Uniting Intensity- and Count-Based Proteomics
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DOI：
10.1021/acs.analchem.9b04375
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发表时间：
2020-05-05
影响因子：
7.4
通讯作者：
Clement, Lieven
中科院分区：
文献类型：
--
作者：
Goeminne, Ludger J. E.;Sticker, Adriaan;Clement, Lieven
缺失值是定量数据依赖质谱的蛋白质组学的主要问题。因此，我们提出了一个创新的解决方案，通过引入一个障碍模型来解决这个关键问题，该模型是二项肽计数和基于肽强度的模型成分的混合物。它可以极大地增强具有许多缺失值的蛋白质的定量，而不必诉诸于对缺失的有害假设。通过与该领域最先进的方法进行比较，我们证明了我们的方法的优越性能。
Missing values are a major issue in quantitative data-dependent mass spectrometry-based proteomics. We therefore present an innovative solution to this key issue by introducing a hurdle model, which is a mixture between a binomial peptide count and a peptide intensity-based model component. It enables dramatically enhanced quantification of proteins with many missing values without having to resort to harmful assumptions for missingness. We demonstrate the superior performance of our method by comparing it with state-of-the-art methods in the field.