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Analysis and Visualization of Quantitative Proteomics Data Using FragPipe-Analyst.
Hsiao, Yi; Zhang, Haijian; Li, Ginny Xiaohe; Deng, Yamei; Yu, Fengchao; Valipour Kahrood, Hossein; Steele, Joel R; Schittenhelm, Ralf B; Nesvizhskii, Alexey I.
Afiliação
  • Hsiao Y; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, United States.
  • Zhang H; Monash Proteomics & Metabolomics Platform, Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, Victoria 3800, Australia.
  • Li GX; Department of Pathology, University of Michigan, Ann Arbor, Michigan 48109, United States.
  • Deng Y; Department of Pathology, University of Michigan, Ann Arbor, Michigan 48109, United States.
  • Yu F; Department of Pathology, University of Michigan, Ann Arbor, Michigan 48109, United States.
  • Valipour Kahrood H; Monash Proteomics & Metabolomics Platform, Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, Victoria 3800, Australia.
  • Steele JR; Monash Genomics & Bioinformatics Platform, Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, Victoria 3800, Australia.
  • Schittenhelm RB; Monash Proteomics & Metabolomics Platform, Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, Victoria 3800, Australia.
  • Nesvizhskii AI; Monash Proteomics & Metabolomics Platform, Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, Victoria 3800, Australia.
J Proteome Res ; 2024 Sep 10.
Article em En | MEDLINE | ID: mdl-39254081
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article