Automated detection of inaccurate and imprecise transitions in peptide quantification by multiple reaction monitoring mass spectrometry.
Automated detection of inaccurate and imprecise transitions in peptide quantification by multiple reaction monitoring mass spectrometry.
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DOI：
10.1373/clinchem.2009.138420
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发表时间：
2010-02
影响因子：
9.3
通讯作者：
Carr SA
中科院分区：
文献类型：
--
作者：
Abbatiello SE;Mani DR;Keshishian H;Carr SA
具有稳定同位素标记的内标物（SIS）的肽的多反应监测质谱（MRM-MS）越来越多地用于开发复杂生物基质中蛋白质的定量测定。这些分析可以是高度精确和定量的，但频繁发生的干扰需要手动审查MRM-MS数据，这是一个容易出现人为错误的时间密集型过程。我们开发了一种算法，可以根据重复样本中干扰信号的存在或回收不一致来识别不准确的转变数据。该算法采用2种正交方法客观评价MRM-MS数据。首先，比较分析物肽与SIS肽的相对产物离子强度，并使用t检验来确定它们是否显著不同。然后根据分析物峰面积与样品重复测定的SIS峰面积的比值计算CV。该算法识别出有问题的转换，并实现了94%-100%的准确性，正确识别错误转换的灵敏度和特异性为83%-100%。该算法是强大的挑战时，多种类型的干扰和有问题的过渡。这种用于自动检测MRM-MS数据中不准确和不精确转换（AuDIT）的算法减少了手动和主观检查数据所需的时间，提高了数据分析的整体准确性，并且易于实施到标准数据分析工作流程中。AuDIT目前使用从MRM-MS数据处理软件包导出的结果，并可作为此类软件中的分析工具实施。
Multiple reaction monitoring mass spectrometry (MRM-MS) of peptides with stable isotope–labeled internal standards (SISs) is increasingly being used to develop quantitative assays for proteins in complex biological matrices. These assays can be highly precise and quantitative, but the frequent occurrence of interferences requires that MRM-MS data be manually reviewed, a time-intensive process subject to human error. We developed an algorithm that identifies inaccurate transition data based on the presence of interfering signal or inconsistent recovery among replicate samples. The algorithm objectively evaluates MRM-MS data with 2 orthogonal approaches. First, it compares the relative product ion intensities of the analyte peptide to those of the SIS peptide and uses a t-test to determine if they are significantly different. A CV is then calculated from the ratio of the analyte peak area to the SIS peak area from the sample replicates. The algorithm identified problematic transitions and achieved accuracies of 94%–100%, with a sensitivity and specificity of 83%–100% for correct identification of errant transitions. The algorithm was robust when challenged with multiple types of interferences and problematic transitions. This algorithm for automated detection of inaccurate and imprecise transitions (AuDIT) in MRM-MS data reduces the time required for manual and subjective inspection of data, improves the overall accuracy of data analysis, and is easily implemented into the standard data-analysis work flow. AuDIT currently works with results exported from MRM-MS data-processing software packages and may be implemented as an analysis tool within such software.
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影响因子：
2.9
作者：
BROWNE, TR
通讯作者：
BROWNE, TR
影响因子：
4.1
作者：
Draisci, R;Palleschi, L;Cammarata, P
通讯作者：
Cammarata, P
影响因子：
9.9
作者：
Lange, Vinzenz;Picotti, Paola;Domon, Bruno;Aebersold, Ruedi
通讯作者：
Aebersold, Ruedi
影响因子：
7.4
作者：
Clauser, KR;Baker, P;Burlingame, AL
通讯作者：
Burlingame, AL
影响因子：
3.3
作者：
Abbatiello, Susan E.;Pan, Yuan-Xiang;Conrads, Thomas P.
通讯作者：
Conrads, Thomas P.