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Analysis and Visualization of Quantitative Proteomics Data Using FragPipe-Analyst.

Authors :
Hsiao Y
Zhang H
Li GX
Deng Y
Yu F
Valipour Kahrood H
Steele JR
Schittenhelm RB
Nesvizhskii AI
Source :
Journal of proteome research [J Proteome Res] 2024 Oct 04; Vol. 23 (10), pp. 4303-4315. Date of Electronic Publication: 2024 Sep 10.
Publication Year :
2024

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.

Details

Language :
English
ISSN :
1535-3907
Volume :
23
Issue :
10
Database :
MEDLINE
Journal :
Journal of proteome research
Publication Type :
Academic Journal
Accession number :
39254081
Full Text :
https://doi.org/10.1021/acs.jproteome.4c00294