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GraphBio: A shiny web app to easily perform popular visualization analysis for omics data
Background: 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. Methods and Results: Herein, we prese...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9490469/ https://www.ncbi.nlm.nih.gov/pubmed/36159985 http://dx.doi.org/10.3389/fgene.2022.957317 |
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author | Zhao, Tianxin Wang, Zelin |
author_facet | Zhao, Tianxin Wang, Zelin |
author_sort | Zhao, Tianxin |
collection | PubMed |
description | Background: 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. Methods and Results: 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. Conclusion: 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. |
format | Online Article Text |
id | pubmed-9490469 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-94904692022-09-22 GraphBio: A shiny web app to easily perform popular visualization analysis for omics data Zhao, Tianxin Wang, Zelin Front Genet Genetics Background: 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. Methods and Results: 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. Conclusion: 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. Frontiers Media S.A. 2022-09-07 /pmc/articles/PMC9490469/ /pubmed/36159985 http://dx.doi.org/10.3389/fgene.2022.957317 Text en Copyright © 2022 Zhao and Wang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Zhao, Tianxin Wang, Zelin GraphBio: A shiny web app to easily perform popular visualization analysis for omics data |
title | GraphBio: A shiny web app to easily perform popular visualization analysis for omics data |
title_full | GraphBio: A shiny web app to easily perform popular visualization analysis for omics data |
title_fullStr | GraphBio: A shiny web app to easily perform popular visualization analysis for omics data |
title_full_unstemmed | GraphBio: A shiny web app to easily perform popular visualization analysis for omics data |
title_short | GraphBio: A shiny web app to easily perform popular visualization analysis for omics data |
title_sort | graphbio: a shiny web app to easily perform popular visualization analysis for omics data |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9490469/ https://www.ncbi.nlm.nih.gov/pubmed/36159985 http://dx.doi.org/10.3389/fgene.2022.957317 |
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