Differential Gene Expression Analysis with Visual Analytics
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Date
2025
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
Differential gene expression (DGE) analysis is one of the most used techniques for RNA-seq data analysis, and it is applied in various medical and biological contexts, including biomarkers for diagnosis and prognosis and evaluation of the effectiveness of specific treatments. The conduction of a DGE analysis typically involves navigating a complex, multi-step pipeline, which usually requires proficiency in programming languages like R. This presents a barrier to researchers like biologists and clinicians, who may have limited or no coding skills, and adds additional overhead even for experienced bioinformaticians. To overcome these challenges, we propose a preliminary visual analytics prototype that simplifies DGE analysis, enabling users to perform the analyses without coding expertise.
Description
CCS Concepts: Human-centered computing → Visual analytics
@inproceedings{10.2312:evp.20251126,
booktitle = {EuroVis 2025 - Posters},
editor = {Diehl, Alexandra and Kucher, Kostiantyn and Médoc, Nicolas},
title = {{Differential Gene Expression Analysis with Visual Analytics}},
author = {Fortunato, Francesco and Santaroni, Cristian and Blasilli, Graziano and Fiscon, Giulia and Lenti, Simone and Santucci, Giuseppe},
year = {2025},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-286-8},
DOI = {10.2312/evp.20251126}
}