| 论文作者 |
Gui, XQ; Huang, J; Ruan, LJ; Wu, YJ; Guo, X; Cao, RF; Zhou, SH; Tan, FX; Zhu, HW; Li, MS; Zhang, GQ; Zhou, H; Zhan, LX; Liu, X; Tu, SQ; Shao, Z |
| 摘要 |
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. |
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