mProphet: automated data processing and statistical validation for large-scale SRM experiments
mProphet: automated data processing and statistical validation for large-scale SRM experiments
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DOI：
10.1038/nmeth.1584
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发表时间：
2011-05-01
期刊：
影响因子：
48
通讯作者：
Aebersold, Ruedi
中科院分区：
文献类型：
--
作者：
Reiter, Lukas;Rinner, Oliver;Aebersold, Ruedi
选择反应监测（SRM）是一种靶向质谱方法，其越来越多地用于蛋白质组学中，以高灵敏度、再现性和准确性检测和定量预选蛋白质组。目前，固体火箭发动机测量数据大多是根据特别标准通过人工检查进行主观评价，无法对不同的数据集进行一致的分析，也无法对其误差率进行客观评估。在这里，我们提出了mProphet，一个全自动系统，计算准确的错误率，用于识别SRM数据集中的靶肽，并通过将数据中的相关特征结合到统计模型中来最大限度地提高特异性和灵敏度。
S elected reaction monitoring (SRM) is a targeted mass spectrometric method that is increasingly used in proteomics for the detection and quantification of sets of preselected proteins at high sensitivity, reproducibility and accuracy. Currently, data from SRM measurements are mostly evaluated subjectively by manual inspection on the basis of ad hoc criteria, precluding the consistent analysis of different data sets and an objective assessment of their error rates. Here we present mProphet, a fully automated system that computes accurate error rates for the identification of targeted peptides in SRM data sets and maximizes specificity and sensitivity by combining relevant features in the data into a statistical model.