AUTHOR=Zhao Tianxin , Wang Zelin 

TITLE=GraphBio: A shiny web app to easily perform popular visualization analysis for omics data

JOURNAL=Frontiers in Genetics

VOLUME=13

YEAR=2022

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2022.957317

DOI=10.3389/fgene.2022.957317

ISSN=1664-8021

ABSTRACT=<p><bold>Background:</bold> Massive amounts of omics data are produced and usually require sophisticated visualization analysis. These analyses often require programming skills, which are difficult for experimental biologists. Thus, more user-friendly tools are urgently needed.</p><p><bold>Methods and Results:</bold> Herein, 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.</p><p><bold>Conclusion:</bold> GraphBio, as an online web application, is freely available at <ext-link ext-link-type="uri" xlink:href="http://www.graphbio1.com/en/" xmlns:xlink="http://www.w3.org/1999/xlink">http://www.graphbio1.com/en/</ext-link> (English version) and <ext-link ext-link-type="uri" xlink:href="http://www.graphbio1.com/" xmlns:xlink="http://www.w3.org/1999/xlink">http://www.graphbio1.com/</ext-link> (Chinese version). The source code of GraphBio is available at <ext-link ext-link-type="uri" xlink:href="https://github.com/databio2022/GraphBio" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/databio2022/GraphBio</ext-link>.</p>