MSstats Version 4.0: Statistical Analyses of Quantitative Mass Spectrometry-Based Proteomic Experiments with Chromatography-Based Quantification at Scale.
MSstats Version 4.0: Statistical Analyses of Quantitative Mass Spectrometry-Based Proteomic Experiments with Chromatography-Based Quantification at Scale.
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DOI：
10.1021/acs.jproteome.2c00834
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发表时间：
2023-05-05
影响因子：
4.4
通讯作者：
Vitek, Olga
中科院分区：
文献类型：
--
作者：
Kohler, Devon;Staniak, Mateusz;Tsai, Tsung-Heng;Huang, Ting;Shulman, Nicholas;Bernhardt, Oliver M.;MacLean, Brendan X.;Nesvizhskii, Alexey I.;Reiter, Lukas;Sabido, Eduard;Choi, Meena;Vitek, Olga
关键词：
MSstats R-Bioconductor系列软件包广泛用于定量自下而上的基于质谱的蛋白质组学实验的统计分析，以检测差异丰富的蛋白质。它适用于各种实验设计和数据采集策略，并与许多用于识别和量化光谱特征的数据处理工具兼容。面对日益复杂的实验和数据处理策略，该家族的核心软件包，同名的MSstats，经历了一系列实质性的更新。它的新版本MSstats v4.0改进了统计方法的可用性、多功能性和准确性，以及计算资源的使用。新的转换器将上游处理工具的输出直接与MSstats集成，用户需要较少的手工工作。软件包的统计模型已经更新为更健壮的工作流。最后，对MSstats的代码进行了实质性的重构，以提高内存使用和计算速度。在这里，我们详细介绍这些更新，突出新旧版本之间的方法差异。将MSstats v4.0与之前的实现以及MSqRob和DEqMS包进行对照混合物和生物实验的实证比较表明，与现有方法相比，MSstats v4.0具有更强的性能和更好的可用性。
The MSstats R-Bioconductor family of packages is widely used for statistical analyses of quantitative bottom-up mass spectrometry-based proteomic experiments to detect differentially abundant proteins. It is applicable to a variety of experimental designs and data acquisition strategies and is compatible with many data processing tools used to identify and quantify spectral features. In the face of ever-increasing complexities of experiments and data processing strategies, the core package of the family, with the same name MSstats, has undergone a series of substantial updates. Its new version MSstats v4.0 improves the usability, versatility, and accuracy of statistical methodology, and the usage of computational resources. New converters integrate the output of upstream processing tools directly with MSstats, requiring less manual work by the user. The package’s statistical models have been updated to a more robust workflow. Finally, MSstats’ code has been substantially refactored to improve memory use and computation speed. Here we detail these updates, highlighting methodological differences between the new and old versions. An empirical comparison of MSstats v4.0 to its previous implementations, as well as to the packages MSqRob and DEqMS, on controlled mixtures and biological experiments demonstrated a stronger performance and better usability of MSstats v4.0 as compared to existing methods.
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影响因子：
7.4
作者：
Goeminne, Ludger J. E.;Sticker, Adriaan;Clement, Lieven
通讯作者：
Clement, Lieven
DOI：
10.1146/annurev-anchem-071015-041535
发表时间：
2016-01-01
期刊：
ANNUAL REVIEW OF ANALYTICAL CHEMISTRY, VOL 9
影响因子：
--
作者：
Gillet, Ludovic C.;Leitner, Alexander;Aebersold, Ruedi
通讯作者：
Aebersold, Ruedi
DOI：
10.1074/mcp.ra120.002105
发表时间：
2020-10
期刊：
Molecular & cellular proteomics : MCP
影响因子：
--
作者：
Huang T;Choi M;Tzouros M;Golling S;Pandya NJ;Banfai B;Dunkley T;Vitek O
通讯作者：
Vitek O
影响因子：
3
作者：
Clough T;Thaminy S;Ragg S;Aebersold R;Vitek O
通讯作者：
Vitek O
影响因子：
7
作者：
Meierhofer, David;Halbach, Melanie;Auburger, Georg
通讯作者：
Auburger, Georg