zMAP工具集：通过方差稳定z变换对大规模蛋白质组数据进行基于模型的分析

IF 10.1 1区生物学 Q1 BIOTECHNOLOGY & APPLIED MICROBIOLOGY

Genome Biology Pub Date : 2024-10-14 DOI:10.1186/s13059-024-03382-9

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

{"title":"zMAP工具集：通过方差稳定z变换对大规模蛋白质组数据进行基于模型的分析","authors":"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","doi":"10.1186/s13059-024-03382-9","DOIUrl":null,"url":null,"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.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"23 1","pages":""},"PeriodicalIF":10.1000,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"zMAP toolset: model-based analysis of large-scale proteomic data via a variance stabilizing z-transformation\",\"authors\":\"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\",\"doi\":\"10.1186/s13059-024-03382-9\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":12611,\"journal\":{\"name\":\"Genome Biology\",\"volume\":\"23 1\",\"pages\":\"\"},\"PeriodicalIF\":10.1000,\"publicationDate\":\"2024-10-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Genome Biology\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1186/s13059-024-03382-9\",\"RegionNum\":1,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BIOTECHNOLOGY & APPLIED MICROBIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Genome Biology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1186/s13059-024-03382-9","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOTECHNOLOGY & APPLIED MICROBIOLOGY","Score":null,"Total":0}

引用次数: 0

摘要

等位标记质谱（ILMS）已被广泛用于在整个蛋白质组范围内量化不同生物条件下蛋白质的相对丰度。然而，大规模 ILMS 数据集通常涉及多次质谱运行，给 ILMS 样品的整合带来了极大的计算困难。我们介绍的zMAP是一个工具集，它通过对相关的均值-方差依赖性建模，并相应地应用方差稳定z变换，使不同质谱运行的ILMS强度具有可比性。zMAP 的实用性在涉及细胞分化动态和癌症患者异质性的几个案例研究中得到了证明。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

zMAP toolset: model-based analysis of large-scale proteomic data via a variance stabilizing z-transformation

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.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Genome Biology Biochemistry, Genetics and Molecular Biology-Genetics

CiteScore

21.00

自引率

3.30%

发文量

241

审稿时长

2 months

期刊介绍： Genome Biology stands as a premier platform for exceptional research across all domains of biology and biomedicine, explored through a genomic and post-genomic lens. With an impressive impact factor of 12.3 (2022),* the journal secures its position as the 3rd-ranked research journal in the Genetics and Heredity category and the 2nd-ranked research journal in the Biotechnology and Applied Microbiology category by Thomson Reuters. Notably, Genome Biology holds the distinction of being the highest-ranked open-access journal in this category. Our dedicated team of highly trained in-house Editors collaborates closely with our esteemed Editorial Board of international experts, ensuring the journal remains on the forefront of scientific advances and community standards. Regular engagement with researchers at conferences and institute visits underscores our commitment to staying abreast of the latest developments in the field.