GraphBio: A shiny web app to easily perform popular visualization analysis for omics data - Zhao, Tianxin; Wang, Zelin (Frontiers in Genetics, 2022)
Background: Massive amount of omics data is produced and usually requires sophisticated visualization analysis. These analyses often require programming skills, which are difficult for experimental biologists. Thus, more user-friendly tools are urgently needed. Methods and Results: Here, we present GraphBio, a shiny web app to easily perform visualization analysis for omics data. GraphBio provides 15 popular visualization analysis methods, including heatmap, volcano plots, MA plots, network plots, dot plots, chord plots, pie plots, four quadrant diagrams, venn diagrams, cumulative distribution curves, principal component analysis (PCA), survival analysis, receiver operating characteristic (ROC) analysis, correlation analysis and text cluster analysis. It enables experimental biologists without programming skills to easily perform popular visualization analysis and get publication-ready figures. Conclusions: GraphBio, as an online web application, is freely available at http://www.graphbio1.com/en/ (English version) and http://www.graphbio1.com/ (Chinese version). The source code of GraphBio is available at https://github.com/databio2022/GraphBio.