Ferretti Daniela, Kyriakidou Pelagia, Xiao Jinqiu, Urazbakhtin Shamil, De Nart Carlo, Cox Jürgen
Computational Systems Biochemistry Research Group, Max Planck Institute of Biochemistry, Am Klopferspitz 18, Martinsried 82152, Germany.
J Proteome Res. 2025 Mar 7;24(3):1219-1229. doi: 10.1021/acs.jproteome.4c00869. Epub 2025 Feb 25.
We present an update of the MaxQuant software for isobaric labeling data and evaluate its performance on benchmark data sets. Impurity correction factors can be applied to labels mixing C- and N-type reporter ions such as TMT Pro. Application to a single-cell multispecies mixture benchmark shows the high accuracy of the impurity-corrected results. TMT data recorded with FAIMS separation can be analyzed directly in MaxQuant without splitting the raw data into separate files per FAIMS voltage. Weighted median normalization is applied to several data sets, including large-scale human body atlas data. In the benchmark data sets, the weighted median normalization either removes or strongly reduces the batch effects between different TMT plexes and results in clustering by biology. In data sets including reference channels, we find that weighted median normalization performs as well or better when the reference channels are ignored and only the sample channel intensities are used, suggesting that the measurement of reference channels is unnecessary when using weighted median normalization in MaxQuant. We demonstrate that MaxQuant including the weighted median normalization performs well on multinotch MS3 data, as well as on phosphorylation data. MaxQuant is freely available for any purpose and can be downloaded from https://www.maxquant.org/.
我们展示了用于等压标记数据的MaxQuant软件的更新版本,并在基准数据集上评估了其性能。杂质校正因子可应用于混合C型和N型报告离子(如TMT Pro)的标签。应用于单细胞多物种混合物基准测试表明,杂质校正后的结果具有很高的准确性。使用FAIMS分离记录的TMT数据可以直接在MaxQuant中进行分析,而无需将原始数据按每个FAIMS电压拆分为单独的文件。加权中位数归一化应用于多个数据集,包括大规模人体图谱数据。在基准数据集中,加权中位数归一化消除或显著减少了不同TMT复合组之间的批次效应,并导致按生物学进行聚类。在包括参考通道的数据集里,我们发现当忽略参考通道而仅使用样品通道强度时,加权中位数归一化的性能同样良好或更佳,这表明在MaxQuant中使用加权中位数归一化时,参考通道的测量是不必要的。我们证明,包括加权中位数归一化在内的MaxQuant在多缺口MS3数据以及磷酸化数据上表现良好。MaxQuant可免费用于任何目的,可从https://www.maxquant.org/下载。