Merge pull request #2538 from sebastian-schaaf/blog_posts_from_quota_…

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usegalaxy.eu use cases 2024: Blog post of Sheu-Tijani Olawale Abogunloko

content/news/2024-05-13-use-case-sheu-tijani-olawale-abogunloko/index.md

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+---
+title: 'UseGalaxy.eu Use Case: Profiling of Tregs in Coronary Artery Disease using RNAseq'
+date: '2024-05-16'
+tease: "A report out of Galaxy Europe's user space, by Sheu-Tijani Olawale Abogunloko"
+tags: [UseCase]
+authors: Sheu Tijani Olawale Abogunloko
+authors_structured:
+- name: "Sheu Tijani Olawale Abogunloko"
+subsites: [eu, pasteur, freiburg, erasmusmc, elixir-it, belgium, genouest]
+main_subsite: eu
+---
+
+With this article we like to share Sheu-Tijani's experience with usegalaxy.eu and its use for his research.
+
+>My name is Sheu-Tijani Olawale Abogunloko, I am researcher in the [Vascular Immunology Lab](https://www.uniklinik-freiburg.de/kardiologie-und-angiologie/forschung/forschung-freiburg/grundlagenforschung/vascular-immunology-pd-dr-d-wolf.html) at the [University Heart Center Freiburg](https://www.uniklinik-freiburg.de/heart-center.html).
+>
+>Our research interest relies on the study of regulatory T cells (Tregs), a specialized T cell subset known for their immunosuppressive function and regulatory role in maintaining immune tolerance at check. Also, because of their plasticity, they can acquire modulatory as well as pathogenic functions. Bulk RNAseq analysis of Tregs in coronary artery disease (CAD) patients involves studying the gene expression profiles of circulating Tregs isolated from individuals with CAD. These profiles help us to understand the molecular mechanisms underlying the course of the disease. However, these analyses involve several steps from the raw data up to the final profiles.
+>
+>Handling large multi-step workflows is indeed a core feature of Galaxy, thus leveraging the analysis of our bulk RNAseq data of Tregs from CAD patients to another level. More generally said, Galaxy provides us with a user-friendly web-based interface for bioinformatic analysis, primarily by streamlining the analysis process and ensuring accessibility, scalability and reproducibility. Thus, we can gather information on the transcriptional changes in Tregs associated with CAD more efficiently, providing insights into the immunological mechanisms underlying the disease. Ultimately, this is paving the way for the development of targeted immunomodulatory therapies and precision medicine approaches for CAD management.