xOmicsShiny: an R Shiny application for cross-omics data analysis and pathway mapping
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| Опубликовано в:: | bioRxiv (Feb 8, 2025) |
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| Главный автор: | |
| Другие авторы: | , , , , , |
| Опубликовано: |
Cold Spring Harbor Laboratory Press
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| Предметы: | |
| Online-ссылка: | Citation/Abstract Full Text - PDF Full text outside of ProQuest |
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| 022 | |a 2692-8205 | ||
| 024 | 7 | |a 10.1101/2025.01.30.635740 |2 doi | |
| 035 | |a 3165215967 | ||
| 045 | 0 | |b d20250208 | |
| 100 | 1 | |a Gao, Benbo | |
| 245 | 1 | |a xOmicsShiny: an R Shiny application for cross-omics data analysis and pathway mapping | |
| 260 | |b Cold Spring Harbor Laboratory Press |c Feb 8, 2025 | ||
| 513 | |a Working Paper | ||
| 520 | 3 | |a We developed xOmicsShiny, a feature-rich R Shiny-powered application that enables biologists to fully explore omics datasets across experiments and data types, with an emphasis on uncovering biological insights at the pathway level. The data merging feature ensures flexible exploration of cross-omics data, such as transcriptomics, proteomics, metabolomics, and lipidomics. The pathway mapping function covers a broad range of databases, including WikiPathways, Reactome, and KEGG pathways. In addition, xOmicsShiny offers several visualization options and analytical tasks in everyday omics data analysis, namely, PCA, Volcano plot, Venn Diagram, Heatmap, WGCNA and advanced clustering analyses. The application employs customizable modules to perform various analyses, generating both interactive plots and publication-ready figures. This dynamic, modular design overcomes the issue of slow loading in R Shiny tools and allows it to be readily expanded by the research and developer community.Competing Interest StatementB.G., Y.H.S., T.L., R.A. and B.Z. are employees of Biogen and hold stocks from the company. X.Z. and W.L. are employees of BioInfoRx, Inc.Footnotes* Revised the description of pathway enrichment analysis and data merging.* https://github.com/interactivereport/xOmicsShiny | |
| 653 | |a Mapping | ||
| 653 | |a Data analysis | ||
| 653 | |a Transcriptomics | ||
| 653 | |a Metabolomics | ||
| 653 | |a Proteomics | ||
| 700 | 1 | |a Sun, Yu H | |
| 700 | 1 | |a Zhang, Xinmin | |
| 700 | 1 | |a Lin, Tinchi | |
| 700 | 1 | |a Li, Wei | |
| 700 | 1 | |a Admanit, Romi | |
| 700 | 1 | |a Zhang, Baohong | |
| 773 | 0 | |t bioRxiv |g (Feb 8, 2025) | |
| 786 | 0 | |d ProQuest |t Biological Science Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3165215967/abstract/embedded/BH75TPHOCCPB476R?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3165215967/fulltextPDF/embedded/BH75TPHOCCPB476R?source=fedsrch |
| 856 | 4 | 0 | |3 Full text outside of ProQuest |u https://www.biorxiv.org/content/10.1101/2025.01.30.635740v2 |