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TOmicsVis: An all-in-one transcriptomic analysis and visualization R package with Shinyapp interface.
Miao, Ben-Ben; Dong, Wei; Han, Zhao-Fang; Luo, Xuan; Ke, Cai-Huan; You, Wei-Wei.
Afiliación
  • Miao BB; State Key Laboratory of Marine Environmental Science, College of Ocean and Earth Sciences Xiamen University Xiamen China.
  • Dong W; Hospital of Stomatology, Guanghua School of Stomatology, Guangdong Provincial Key Laboratory of Stomatology Sun Yat-Sen University Guangzhou China.
  • Han ZF; State Key Laboratory of Marine Environmental Science, College of Ocean and Earth Sciences Xiamen University Xiamen China.
  • Luo X; State Key Laboratory of Marine Environmental Science, College of Ocean and Earth Sciences Xiamen University Xiamen China.
  • Ke CH; State Key Laboratory of Marine Environmental Science, College of Ocean and Earth Sciences Xiamen University Xiamen China.
  • You WW; State Key Laboratory of Marine Environmental Science, College of Ocean and Earth Sciences Xiamen University Xiamen China.
Imeta ; 2(4): e137, 2023 Nov.
Article en En | MEDLINE | ID: mdl-38868229
ABSTRACT
Transcriptomic analysis has been widely used in comparative experiments to uncover biological mechanisms in various species. However, a simple tool is still lacking to optimize and integrate the features from multiple R packages. In this study, we developed TOmicsVis (Transcriptomics Visualization) (CRAN https//cran.r-project.org/package=TOmicsVis, v2.0.0), an R package that provides a comprehensive solution for transcriptomics analysis and visualization. It utilizes 46 R packages to design 40 suitable functions for the streamlined analysis of multigroup transcriptomic projects, which covers six main categories Sample Statistics, Traits Analysis, Differential Expression, Advanced Analysis, GO and KEGG Enrichment, and Table Operation. TOmicsVis can be performed either locally or online (https//shiny.hiplot.cn/tomicsvis-shiny/), which provides significant convenience for researchers without coding training. These user-friendly visualization functions and built-in analysis capabilities enable researchers to monitor experimental data dynamics promptly and explore transcriptomics data quickly.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Imeta Año: 2023 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Imeta Año: 2023 Tipo del documento: Article
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