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Automated statistical analysis of protein abundance ratios from data generated by stable-isotope dilution and tandem mass spectrometry

机译:根据稳定同位素稀释和串联质谱法生成的数据对蛋白质丰度比进行自动统计分析

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We describe an algorithm for the automated statistical analysis of protein abundance ratios (ASAPRatio) of proteins contained in two samples. Proteins are labeled with distinct stable-isotope tags and fragmented, and the tagged peptide fragments are separated by liquid chromatography (LC) and analyzed by electrospray ionization (ESI) tandem mass spectrometry (MS/MS). The algorithm utilizes the signals recorded for the different isotopic forms of peptides of identical sequence and numerical and statistical methods, such as Savitzky-Golay smoothing filters, statistics for weighted samples, and Dixon's test for outliers, to evaluate protein abundance ratios and their associated errors. The algorithm also provides a statistical assessment to distinguish proteins of significant abundance changes from a population of proteins of unchanged abundance. To evaluate its performance, two sets of LC-ESI-MS/MS data were analyzed by the ASAPRatio algorithm without human intervention, and the data were related to the expected and manually validated values. The utility of the ASAPRatio program was clearly demonstrated by its speed and the accuracy of the generated protein abundance ratios and by its capability to identify specific core components of the RNA polymerase II transcription complex within a high background of copurifying proteins. [References: 30]
机译:我们描述了一种算法,用于两个样本中包含的蛋白质的蛋白质丰度比(ASAPRatio)的自动统计分析。蛋白质用独特的稳定同位素标记物标记并片段化,标记的肽片段通过液相色谱(LC)分离,并通过电喷雾电离(ESI)串联质谱(MS / MS)进行分析。该算法利用针对相同序列的不同同位素形式的肽所记录的信号以及数字和统计方法(例如Savitzky-Golay平滑滤波器,加权样本的统计数据和离群值的Dixon检验)来评估蛋白质丰度比及其相关的误差。该算法还提供了统计评估,以将丰度变化显着的蛋白质与丰度不变的蛋白质群区分开。为了评估其性能,在没有人工干预的情况下,通过ASAPRatio算法分析了两组LC-ESI-MS / MS数据,并将这些数据与预期值和手动验证值相关。 ASAPRatio程序的实用性已通过其速度和生成的蛋白质丰度比的准确性以及在高共纯化蛋白质背景下鉴定RNA聚合酶II转录复合物的特定核心成分的能力得到了明确证明。 [参考:30]

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