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

Hiba Ben Aribi; Imraan Dixon; Najla Abassi; Olaitan I Awe

doi:10.1038/s41598-025-93067-5

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

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

Authors

Hiba Ben Aribi¹, Imraan Dixon², Najla Abassi³, Olaitan I Awe^{4

5}

Affiliations

¹ Faculty of Sciences of Tunis, University of Tunis El Manar, Tunis, Tunisia. benaribi.hiba@gmail.com.
² Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.
³ Higher Institute of Biotechnology Sidi Thabet, Manouba University, Manouba, Tunisia.
⁴ Department of Computer Science, University of Ibadan, Ibadan, Oyo State, Nigeria.
⁵ African Society for Bioinformatics and Computational Biology, Cape Town, South Africa.

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.

MeSH terms

Animals
Computational Biology* / methods
Gene Expression Profiling* / methods
Gene Expression*
Genetic Variation*
Genomics / methods
Humans
Sequence Analysis, RNA / methods
Software*