ArticleiMeta2023
TOmicsVis: An all-in-one transcriptomic analysis and visualization R package with Shinyapp interface.
Article in iMeta, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed.
- Transcriptomic Differences Between TwoJournal of fungi (Basel, Switzerland) · 2026Article
- aplot: Simplifying the creation of complex graphs to visualize associations across diverse data types.Innovation (Cambridge (Mass.)) · 2025Article
- Systematic Identification of Mitochondrial Signatures in Alzheimer's Disease and Inflammatory Bowel Disease.Molecular neurobiology · 2025Article
- ImageGP 2 for enhanced data visualization and reproducible analysis in biomedical research.iMeta · 2024Article
- Comparative Genome-Wide Identification of thePlants (Basel, Switzerland) · 2024Article
- TOmicsVis: An all-in-one transcriptomic analysis and visualization R package with Shinyapp interface.iMeta · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.