Hsiao Yi, Zhang Haijian, Li Ginny Xiaohe, Deng Yamei, Yu Fengchao, Kahrood Hossein Valipour, Steele Joel R, Schittenhelm Ralf B, Nesvizhskii Alexey I
Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
Monash Proteomics & Metabolomics Platform, Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, Victoria 3800, Australia.
bioRxiv. 2024 Mar 10:2024.03.05.583643. doi: 10.1101/2024.03.05.583643.
The FragPipe computational proteomics platform is gaining widespread popularity among the proteomics research community because of its fast processing speed and user-friendly graphical interface. Although FragPipe produces well-formatted output tables that are ready for analysis, there is still a need for an easy-to-use and user-friendly downstream statistical analysis and visualization tool. FragPipe-Analyst addresses this need by providing an R shiny web server to assist FragPipe users in conducting downstream analyses of the resulting quantitative proteomics data. It supports major quantification workflows including label-free quantification, tandem mass tags, and data-independent acquisition. FragPipe-Analyst offers a range of useful functionalities, such as various missing value imputation options, data quality control, unsupervised clustering, differential expression (DE) analysis using Limma, and gene ontology and pathway enrichment analysis using Enrichr. To support advanced analysis and customized visualizations, we also developed FragPipeAnalystR, an R package encompassing all FragPipe-Analyst functionalities that is extended to support site-specific analysis of post-translational modifications (PTMs). FragPipe-Analyst and FragPipeAnalystR are both open-source and freely available.
FragPipe计算蛋白质组学平台因其快速的处理速度和用户友好的图形界面而在蛋白质组学研究社区中广受欢迎。尽管FragPipe生成了格式良好、可供分析的输出表格,但仍需要一个易于使用且用户友好的下游统计分析和可视化工具。FragPipe-Analyst通过提供一个R shiny网络服务器来满足这一需求,以帮助FragPipe用户对所得的定量蛋白质组学数据进行下游分析。它支持主要的定量工作流程,包括无标记定量、串联质量标签和数据非依赖采集。FragPipe-Analyst提供了一系列有用的功能,如各种缺失值插补选项、数据质量控制、无监督聚类、使用Limma进行差异表达(DE)分析,以及使用Enrichr进行基因本体和通路富集分析。为了支持高级分析和定制可视化,我们还开发了FragPipeAnalystR,这是一个R包,包含了所有FragPipe-Analyst的功能,并进行了扩展以支持翻译后修饰(PTM)的位点特异性分析。FragPipe-Analyst和FragPipeAnalystR都是开源且免费可用的。