ABSTRACT
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.
Competing Interest Statement
A.I.N. and F.Y. receive royalties from the University of Michigan for the sale of MSFragger and IonQuant software licenses to commercial entities. All license transactions are managed by the University of Michigan Innovation Partnerships office and all proceeds are subject to university technology transfer policy. The other authors have no competing interests to declare.
ABBREVIATIONS
- PTM
- post-translational modification
- DDA
- data-dependent acquisition
- DIA
- data-independent acquisition
- LFQ
- label-free quantification
- RCC
- renal cell carcinoma
- ccRCC
- clear cell renal cell carcinoma
- ChRCC
- chromophobe renal cell carcinoma
