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ProteoModlR for functional proteomic analysis

机译:用于功能蛋白质组学分析的ProteoModlR

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Background High-accuracy mass spectrometry enables near comprehensive quantification of the components of the cellular proteomes, increasingly including their chemically modified variants. Likewise, large-scale libraries of quantified synthetic peptides are becoming available, enabling absolute quantification of chemically modified proteoforms, and therefore systems-level analyses of changes of their absolute abundance and stoichiometry. Existing computational methods provide advanced tools for mass spectral analysis and statistical inference, but lack integrated functions for quantitative analysis of post-translationally modified proteins and their modification stoichiometry. Results Here, we develop ProteoModlR, a program for quantitative analysis of abundance and stoichiometry of post-translational chemical modifications across temporal and steady-state biological states. While ProteoModlR is intended for the analysis of experiments using isotopically labeled reference peptides for absolute quantitation, it also supports the analysis of labeled and label-free data, acquired in both data-dependent and data-independent modes for relative quantitation. Moreover, ProteoModlR enables functional analysis of sparsely sampled quantitative mass spectrometry experiments by inferring the missing values from the available measurements, without imputation. The implemented architecture includes parsing and normalization functions to control for common sources of technical variation. Finally, ProteoModlR’s modular design and interchangeable format are optimally suited for integration with existing computational proteomics tools, thereby facilitating comprehensive quantitative analysis of cellular signaling. Conclusions ProteoModlR and its documentation are available for download at http://github.com/kentsisresearchgroup/ProteoModlR as a stand-alone R package.
机译:背景技术高精度质谱法能够对细胞蛋白质组学的成分进行近乎全面的量化,包括其化学修饰的变体。同样,可以使用大规模的合成肽定量库,从而可以对化学修饰的蛋白形式进行绝对定量,从而可以对其绝对丰度和化学计量的变化进行系统级分析。现有的计算方法为质谱分析和统计推断提供了先进的工具,但是缺少用于定量分析翻译后修饰蛋白及其修饰化学计量的集成功能。结果在这里,我们开发了ProteoModlR,该程序用于定量分析跨时间和稳态生物学状态的翻译后化学修饰的丰度和化学计量。尽管ProteoModlR用于使用同位素标记的参考肽进行绝对定量的实验分析,但它也支持标记和无标记数据的分析,以相对于数据的数据依赖和独立于数据的方式获取。而且,ProteoModlR可以通过从可用测量值中推断出缺失值而无需进行归类,从而对稀疏采样的定量质谱实验进行功能分析。已实现的体系结构包括解析和规范化功能,以控制常见的技术变化来源。最后,ProteoModlR的模块化设计和可互换格式最适合与现有的计算蛋白质组学工具集成,从而有助于对细胞信号进行全面的定量分析。结论ProteoModlR及其文档可作为独立的R包从http://github.com/kentsisresearchgroup/ProteoModlR下载。

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