zMAP toolset: model-based analysis of large-scale proteomic data via a variance stabilizing z-transformation
Abstract 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 computatio...
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| Format: | Article |
| Language: | English |
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BMC
2024-10-01
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| Series: | Genome Biology |
| Online Access: | https://doi.org/10.1186/s13059-024-03382-9 |
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| author | Xiuqi Gui Jing Huang Linjie Ruan Yanjun Wu Xuan Guo Ruifang Cao Shuhan Zhou Fengxiang Tan Hongwen Zhu Mushan Li Guoqing Zhang Hu Zhou Lixing Zhan Xin Liu Shiqi Tu Zhen Shao |
| author_facet | Xiuqi Gui Jing Huang Linjie Ruan Yanjun Wu Xuan Guo Ruifang Cao Shuhan Zhou Fengxiang Tan Hongwen Zhu Mushan Li Guoqing Zhang Hu Zhou Lixing Zhan Xin Liu Shiqi Tu Zhen Shao |
| author_sort | Xiuqi Gui |
| collection | DOAJ |
| description | Abstract 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. |
| format | Article |
| id | doaj-art-fe7c834f206441fa942fc533108154fe |
| institution | OA Journals |
| issn | 1474-760X |
| language | English |
| publishDate | 2024-10-01 |
| publisher | BMC |
| record_format | Article |
| series | Genome Biology |
| spelling | doaj-art-fe7c834f206441fa942fc533108154fe2025-08-20T02:17:47ZengBMCGenome Biology1474-760X2024-10-0125113010.1186/s13059-024-03382-9zMAP toolset: model-based analysis of large-scale proteomic data via a variance stabilizing z-transformationXiuqi Gui0Jing Huang1Linjie Ruan2Yanjun Wu3Xuan Guo4Ruifang Cao5Shuhan Zhou6Fengxiang Tan7Hongwen Zhu8Mushan Li9Guoqing Zhang10Hu Zhou11Lixing Zhan12Xin Liu13Shiqi Tu14Zhen Shao15CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of SciencesCAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of SciencesKey Laboratory of Epigenetic Regulation and Intervention, Shanghai Institute of Biochemistry and Cell Biology, CAS Center for Excellence in Molecular Cell Science, University of Chinese Academy of Sciences, Chinese Academy of SciencesCAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of SciencesCAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of SciencesCAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of SciencesCAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of SciencesCAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of SciencesAnalytical Research Center for Organic and Biological Molecules, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of SciencesDepartment of Statistics, The Pennsylvania State UniversityCAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of SciencesAnalytical Research Center for Organic and Biological Molecules, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of SciencesCAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of SciencesKey Laboratory of Epigenetic Regulation and Intervention, Shanghai Institute of Biochemistry and Cell Biology, CAS Center for Excellence in Molecular Cell Science, University of Chinese Academy of Sciences, Chinese Academy of SciencesCAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of SciencesCAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of SciencesAbstract 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.https://doi.org/10.1186/s13059-024-03382-9 |
| spellingShingle | Xiuqi Gui Jing Huang Linjie Ruan Yanjun Wu Xuan Guo Ruifang Cao Shuhan Zhou Fengxiang Tan Hongwen Zhu Mushan Li Guoqing Zhang Hu Zhou Lixing Zhan Xin Liu Shiqi Tu Zhen Shao zMAP toolset: model-based analysis of large-scale proteomic data via a variance stabilizing z-transformation Genome Biology |
| title | zMAP toolset: model-based analysis of large-scale proteomic data via a variance stabilizing z-transformation |
| title_full | zMAP toolset: model-based analysis of large-scale proteomic data via a variance stabilizing z-transformation |
| title_fullStr | zMAP toolset: model-based analysis of large-scale proteomic data via a variance stabilizing z-transformation |
| title_full_unstemmed | zMAP toolset: model-based analysis of large-scale proteomic data via a variance stabilizing z-transformation |
| title_short | zMAP toolset: model-based analysis of large-scale proteomic data via a variance stabilizing z-transformation |
| title_sort | zmap toolset model based analysis of large scale proteomic data via a variance stabilizing z transformation |
| url | https://doi.org/10.1186/s13059-024-03382-9 |
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