ArticleScientific reports2025
Efficient and easy gene expression and genetic variation data analysis and visualization using exvar.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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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
5 citing papers in PubMed.
- MARVpred: machine learning prediction of inhibitors targeting Marburg virus Gene 4 Small ORF protein.BMC infectious diseases · 2026Article
- RareInsight simplifies the communication of genetic results for rare disease patients.Scientific reports · 2025Article
- EMImR: a Shiny application for identifying transcriptomic and epigenomic changes.GigaByte (Hong Kong, China) · 2025Article
- Enhanced deep Convolutional Neural Network for SARS-CoV-2 variants classification.Frontiers in artificial intelligence · 2025Article
- NeuroVar: an open-source tool for the visualization of gene expression and variation data for biomarkers of neurological diseases.GigaByte (Hong Kong, China) · 2024Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
RNA sequencing data manipulation workflows are complex and require various skills and tools. This creates the need for user-friendly and integrated genomic data analysis and visualization tools. We developed a novel R package using multiple Cran and Bioconductor packages to perform gene expression analysis and genetic variant calling from RNA sequencing data. Multiple public datasets were analyzed using the developed package to validate the pipeline for all the supported species. The developed R package, named "exvar", includes multiple data analysis functions and three data visualization shiny apps integrated as functions. Also, it could be used to analyze several species' data. The exvar package is available in the project's GitHub repository ( https://github.com/omicscodeathon/exvar ).
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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.