GigabyteBioinformaticsPeer-reviewed journal article
EMImR: a Shiny Application for Identifying Transcriptomic and Epigenomic Changes
Hiba Ben AribiiD, Careen NaitoreiD, Farah AyadiiD, Souheila GuerboujiD, Olaitan Igbagbo AweiD
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 miRNA. 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).
- assay: bulk RNA-seq
- assay: DNA methylation
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: database / resource
- research focus: software / tool
- approach: statistical model
- approach: experimental assay
- Citations
- 2
- FWCI
- 0.60
- Field percentile
- top 36%
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