ArticleBioinformatics (Oxford, England)2018
PANDA-view: an easy-to-use tool for statistical analysis and visualization of quantitative proteomics data.
Article in Bioinformatics (Oxford, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- A Bayesian framework for multivariate differential analysis.PLoS computational biology · 2026Article
- The coming era of proteomics-driven precision medicine.National science review · 2025Review
- Target protein identification in live cells and organisms with a non-diffusive proximity tagging system.eLife · 2024Article
- ExpOmics: a comprehensive web platform empowering biologists with robust multi-omics data analysis capabilities.Bioinformatics (Oxford, England) · 2024Article
- Towards a More Accurate Differential Analysis of Multiple Imputed Proteomics Data with mi4limma.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Accounting for multiple imputation-induced variability for differential analysis in mass spectrometry-based label-free quantitative proteomics.PLoS computational biology · 2022Article
- ImShot: An Open-Source Software for Probabilistic Identification of Proteins In Situ and Visualization of Proteomics Data.Molecular & cellular proteomics : MCP · 2022Article
- OmicsOne: associate omics data with phenotypes in one-click.Clinical proteomics · 2021Article
- Article
- Multiple Imputation Approaches Applied to the Missing Value Problem in Bottom-Up Proteomics.International journal of molecular sciences · 2021Article
- PeptideWitch-A Software Package to Produce High-Stringency Proteomics Data Visualizations from Label-Free Shotgun Proteomics Data.Proteomes · 2020Article
- Small Noncoding RNA CjNC110 Influences Motility, Autoagglutination, AI-2 Localization, Hydrogen Peroxide Sensitivity, and Chicken Colonization in Campylobacter jejuni.Infection and immunity · 2020Article
- CAncer bioMarker Prediction Pipeline (CAMPP)-A standardized framework for the analysis of quantitative biological data.PLoS computational biology · 2020Article
- Quantitative Analyses Reveal Novel Roles formBio · 2019Article
- PANDA: A comprehensive and flexible tool for quantitative proteomics data analysis.Bioinformatics (Oxford, England) · 2019Article
Corrections and comments
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Authors and funding
8 authors.
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Abstract
Summary: Compared with the numerous software tools developed for identification and quantification of -omics data, there remains a lack of suitable tools for both downstream analysis and data visualization. To help researchers better understand the biological meanings in their -omics data, we present an easy-to-use tool, named PANDA-view, for both statistical analysis and visualization of quantitative proteomics data and other -omics data. PANDA-view contains various kinds of analysis methods such as normalization, missing value imputation, statistical tests, clustering and principal component analysis, as well as the most commonly-used data visualization methods including an interactive volcano plot. Additionally, it provides user-friendly interfaces for protein-peptide-spectrum representation of the quantitative proteomics data. Availability and implementation: PANDA-view is freely available at https://sourceforge.net/projects/panda-view/. Supplementary information: Supplementary data are available at Bioinformatics online.
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