Ziyi Li, Cory A Weller, Syed Shah, Nicholas L Johnson, Ying Hao, Paige B Jarreau, Jessica Roberts, Deyaan Guha, Colleen Bereda, Sydney Klaisner, Pedro Machado, Matteo Zanovello, Mercedes Prudencio, Björn Oskarsson, Nathan P Staff, Dennis W Dickson, Pietro Fratta, Leonard Petrucelli, Priyanka Narayan, Mark R Cookson, Michael E Ward, Andrew B Singleton, Mike A Nalls, Yue A Qi
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引用次数: 0
摘要
质谱(MS)是一种广泛应用于蛋白质鉴定和表征的技术,在个性化医疗、系统生物学和生物医学方面都有应用。基于质谱的蛋白质组学的应用促进了我们对蛋白质功能、细胞信号传导和复杂生物系统的了解。质谱数据分析是一个关键过程,包括蛋白质和肽的鉴定和定量,然后在下游分析中探索其生物功能。为了解决 MS 数据分析的复杂性,我们开发了 ProtPipe,以简化和自动化预装 DIA-NN 的高通量蛋白质组学和多肽组学数据集的处理和分析。该管道有助于数据质量控制、样品过滤和归一化,确保下游分析稳健可靠。ProtPipe 提供下游分析,包括蛋白质和多肽差异丰度鉴定、通路富集分析、蛋白质-蛋白质相互作用分析以及主要组织相容性复合体 (MHC) - 多肽结合亲和力分析。ProtPipe 通过执行统计后处理和计算实验设计中预定义配对条件之间的折叠变化,生成带注释的表格和可视化效果。它是一个开源的、文档齐全的工具,可在 https://github.com/NIH-CARD/ProtPipe 上在线获取,具有用户友好的 Web 界面。
ProtPipe: A Multifunctional Data Analysis Pipeline for Proteomics and Peptidomics.
Mass spectrometry (MS) is a technique widely employed for the identification and characterization of proteins, with personalized medicine, systems biology, and biomedical applications. The application of MS-based proteomics advances our understanding of protein function, cellular signaling, and complex biological systems. MS data analysis is a critical process that includes identifying and quantifying proteins and peptides and then exploring their biological functions in downstream analysis. To address the complexities associated with MS data analysis, we developed ProtPipe to streamline and automate the processing and analysis of high-throughput proteomics and peptidomics datasets with DIA-NN preinstalled. The pipeline facilitates data quality control, sample filtering, and normalization, ensuring robust and reliable downstream analyses. ProtPipe provides downstream analyses, including protein and peptide differential abundance identification, pathway enrichment analysis, protein-protein interaction analysis, and Major histocompatibility complex (MHC) -peptide binding affinity analysis. ProtPipe generates annotated tables and visualizations by performing statistical postprocessing and calculating fold changes between predefined pairwise conditions in an experimental design. It is an open-source, well-documented tool available online at https://github.com/NIH-CARD/ProtPipe, with a user-friendly web interface.