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Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools
Published on: August 19, 2025
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PANDA-view: an easy-to-use tool for statistical analysis and visualization of quantitative proteomics data
Cheng Chang1, Kaikun Xu1, Chaoping Guo2
1State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Lifeomics, National Center for Protein Sciences (Beijing), Beijing, People's Republic of China.
Bioinformatics (Oxford, England)
|May 24, 2018
Summary
Researchers can now analyze and visualize omics data with PANDA-view, a new software tool. This tool offers statistical analysis and interactive visualization for proteomics and other omics datasets.
Area of Science:
- Bioinformatics
- Computational Biology
- Proteomics
Background:
- Numerous software tools exist for omics data identification and quantification.
- A gap remains in user-friendly tools for downstream analysis and data visualization of omics data.
Purpose of the Study:
- To present PANDA-view, an easy-to-use software tool for statistical analysis and data visualization of quantitative proteomics and other omics data.
- To facilitate researchers' understanding of biological meanings within their omics data.
Main Methods:
- PANDA-view integrates various statistical analysis methods: normalization, missing value imputation, statistical tests, clustering, and principal component analysis.
- Includes commonly used data visualization methods, such as interactive volcano plots.
- Provides user-friendly interfaces for protein-peptide-spectrum representation of quantitative proteomics data.
Main Results:
- PANDA-view offers a comprehensive suite of tools for both statistical analysis and visualization.
- The software supports various omics data types beyond proteomics.
- Interactive features, like volcano plots, enhance data interpretation.
Conclusions:
- PANDA-view addresses the need for integrated downstream analysis and visualization tools in omics research.
- The tool empowers researchers to explore and interpret complex omics datasets more effectively.
- PANDA-view is freely available, promoting accessibility in the scientific community.
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