EMImR: a Shiny application for identifying transcriptomic and epigenomic changes

Identifying differentially expressed genes associated with genetic pathologies is crucial to understanding the biological differences between healthy and diseased states and identifying potential biomarkers and therapeutic targets. However, gene expression profiles are controlled by various mechanisms, including epigenomic changes, such as DNA methylation, histone modifications, and interfering microRNA silencing. We developed a novel Shiny application for transcriptomic and epigenomic change identification and correlation using a combination of Bioconductor and CRAN packages. The developed package, named EMImR, is a user-friendly tool with an easy-to-use graphical user interface to identify differentially expressed genes, differentially methylated genes, and differentially expressed interfering microRNA. In addition, it identifies the correlation between transcriptomic and epigenomic modifications and performs the ontology analysis of genes of interest. The developed tool could be used to study the regulatory effects of epigenetic factors. The application is publicly available in the GitHub repository (https://github.com/omicscodeathon/emimr).

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Publication Details

Journal
Gigabyte
Published
2025-10-30
DOI
https://doi.org/10.46471/gigabyte.168
Citations
1
Primary Topic
Epigenetics and DNA Methylation
Type
article
Field-Weighted Citation Impact
0.81

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article

EMImR: a Shiny application for identifying transcriptomic and epigenomic changes

Hiba Ben Aribi, Souheila Guerbouj, F. Makni Ayadi, Careen Naitore et al.
1 citations
Gigabyte
Epigenetics and DNA Methylation
0.81
article

EMImR: a Shiny application for identifying transcriptomic and epigenomic changes

Hiba Ben Aribi, Souheila Guerbouj, F. Makni Ayadi, Careen Naitore, Olaitan Igbagbo Awe
article en
1 citations

Abstract

Identifying differentially expressed genes associated with genetic pathologies is crucial to understanding the biological differences between healthy and diseased states and identifying potential biomarkers and therapeutic targets. However, gene expression profiles are controlled by various mechanisms, including epigenomic changes, such as DNA methylation, histone modifications, and interfering microRNA silencing. We developed a novel Shiny application for transcriptomic and epigenomic change identification and correlation using a combination of Bioconductor and CRAN packages. The developed package, named EMImR, is a user-friendly tool with an easy-to-use graphical user interface to identify differentially expressed genes, differentially methylated genes, and differentially expressed interfering microRNA. In addition, it identifies the correlation between transcriptomic and epigenomic modifications and performs the ontology analysis of genes of interest. The developed tool could be used to study the regulatory effects of epigenetic factors. The application is publicly available in the GitHub repository (https://github.com/omicscodeathon/emimr).

GigabyteVol. 2025
University of Ibadan (NG), Jomo Kenyatta University of Agriculture and Technology (KE), Tunis El Manar University (TN)
National Institutes of Health
Openalex Percentile: Top 22%
Epigenetics and DNA Methylation
0.81
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