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. 2025 Apr 10;15(1):12264.
doi: 10.1038/s41598-025-93067-5.

Efficient and easy gene expression and genetic variation data analysis and visualization using exvar

Hiba Ben Aribi  1 , Imraan Dixon  2 , Najla Abassi  3 , Olaitan I Awe  4   5
Affiliations

Efficient and easy gene expression and genetic variation data analysis and visualization using exvar

Hiba Ben Aribi et al. Sci Rep. .

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 ).

Keywords: CNVs; Exvar; Gene expression; Indels; R package; SNPs; Variants calling.

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Conflict of interest statement

Declarations. Competing interests: The authors declare no competing interests. Reporting issues: To report an issue please use the issues page ( https://github.com/omicscodeathon/exvar/issues ). Please check existing issues before submitting a new one. Contribute to the project: You can offer to help with the further development of this project by making pull requests on the project’s GitHub repository. To do so, fork the exvar GitHub repository and make the proposed changes. Once completed and tested, submit a pull request to the exvar GitHub repository.

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