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SBGNview: towards data analysis, integration and visualization on all pathways
SUMMARY: Pathway analysis is widely used in genomics and omics research, but the data visualization has been highly limited in function, pathway coverage and data format. Here, we develop SBGNview a comprehensive R package to address these needs. By adopting the standard SBGN format, SBGNview greatl...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8826166/ https://www.ncbi.nlm.nih.gov/pubmed/34864890 http://dx.doi.org/10.1093/bioinformatics/btab793 |
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author | Dong, Xiaoxi Vegesna, Kovidh Brouwer, Cory Luo, Weijun |
author_facet | Dong, Xiaoxi Vegesna, Kovidh Brouwer, Cory Luo, Weijun |
author_sort | Dong, Xiaoxi |
collection | PubMed |
description | SUMMARY: Pathway analysis is widely used in genomics and omics research, but the data visualization has been highly limited in function, pathway coverage and data format. Here, we develop SBGNview a comprehensive R package to address these needs. By adopting the standard SBGN format, SBGNview greatly extend the coverage of pathway-based analysis and data visualization to essentially all major pathway databases beyond KEGG, including 5200 reference pathways and over 3000 species. In addition, SBGNview substantially extends or exceeds current tools (esp. Pathview) in both design and function, including standard input format (SBGN), high-quality output graphics (SVG format) convenient for both interpretation and further update, and flexible and open-end workflow for iterative editing and interactive visualization (Highlighter module). In addition to pathway analysis and data visualization, SBGNview provides essential infrastructure for SBGN data manipulation and processing. AVAILABILITY AND IMPLEMENTATION: The data underlying this article are available as part of the SBGNview package is available on both GitHub and Bioconductor: https://github.com/datapplab/SBGNview, https://bioconductor.org/packages/SBGNview. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-8826166 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-88261662022-02-09 SBGNview: towards data analysis, integration and visualization on all pathways Dong, Xiaoxi Vegesna, Kovidh Brouwer, Cory Luo, Weijun Bioinformatics Applications Notes SUMMARY: Pathway analysis is widely used in genomics and omics research, but the data visualization has been highly limited in function, pathway coverage and data format. Here, we develop SBGNview a comprehensive R package to address these needs. By adopting the standard SBGN format, SBGNview greatly extend the coverage of pathway-based analysis and data visualization to essentially all major pathway databases beyond KEGG, including 5200 reference pathways and over 3000 species. In addition, SBGNview substantially extends or exceeds current tools (esp. Pathview) in both design and function, including standard input format (SBGN), high-quality output graphics (SVG format) convenient for both interpretation and further update, and flexible and open-end workflow for iterative editing and interactive visualization (Highlighter module). In addition to pathway analysis and data visualization, SBGNview provides essential infrastructure for SBGN data manipulation and processing. AVAILABILITY AND IMPLEMENTATION: The data underlying this article are available as part of the SBGNview package is available on both GitHub and Bioconductor: https://github.com/datapplab/SBGNview, https://bioconductor.org/packages/SBGNview. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2021-11-23 /pmc/articles/PMC8826166/ /pubmed/34864890 http://dx.doi.org/10.1093/bioinformatics/btab793 Text en © The Author(s) 2021. Published by Oxford University Press. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Applications Notes Dong, Xiaoxi Vegesna, Kovidh Brouwer, Cory Luo, Weijun SBGNview: towards data analysis, integration and visualization on all pathways |
title | SBGNview: towards data analysis, integration and visualization on all pathways |
title_full | SBGNview: towards data analysis, integration and visualization on all pathways |
title_fullStr | SBGNview: towards data analysis, integration and visualization on all pathways |
title_full_unstemmed | SBGNview: towards data analysis, integration and visualization on all pathways |
title_short | SBGNview: towards data analysis, integration and visualization on all pathways |
title_sort | sbgnview: towards data analysis, integration and visualization on all pathways |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8826166/ https://www.ncbi.nlm.nih.gov/pubmed/34864890 http://dx.doi.org/10.1093/bioinformatics/btab793 |
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