Isobaric labeling-based mass spectrometry (ILMS) has been widely used to quantify, on a proteome-wide scale, the relative protein abundance in different biological conditions. However, large-scale ILMS data sets typically involve multiple runs of mass spectrometry, bringing great computational difficulty to the integration of ILMS samples. We present zMAP, a toolset that makes ILMS intensities comparable across mass spectrometry runs by modeling the associated mean-variance dependence and accordingly applying a variance stabilizing z-transformation. The practical utility of zMAP is demonstrated in several case studies involving the dynamics of cell differentiation and the heterogeneity across cancer patients.

中文翻译：

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zMAP 工具集：通过方差稳定 z 变换对大规模蛋白质组学数据进行基于模型的分析


基于同量异位标记的质谱法 （ILMS） 已被广泛用于在蛋白质组范围的范围内量化不同生物条件下的相对蛋白质丰度。然而，大规模 ILMS 数据集通常涉及多次质谱分析，这给 ILMS 样品的整合带来了极大的计算难度。我们提出了 zMAP，这是一个工具集，通过对相关的均值-方差依赖性进行建模并相应地应用方差稳定 z 变换，使 ILMS 强度在质谱运行中具有可比性。zMAP 的实际效用在涉及细胞分化动力学和癌症患者异质性的几个案例研究中得到了证明。