ClusterGVis: An Advanced Visualization and Clustering Tool for Gene Expression Analysis

Both single-cell RNA sequencing and bulk RNA sequencing data provide valuable insights into physiological and pathological processes. The effective interpretation of such data relies on the availability of sophisticated analytical and visualization tools. Here, we introduce ClusterGVis, an advanced bioinformatics software specifically designed to simplify the analysis and visualization of gene expression data. ClusterGVis provides a user-friendly interface that allows researchers to perform fuzzy c-means and k-means clustering on transcriptomic data. It enables researchers to effectively uncover patterns and relationships within complex gene expression profiles. The integrated heatmap visualization features support intuitive exploration of co-expression networks and identification of differentially expressed genes across diverse experimental conditions. ClusterGVis serves a dual purpose: aiding in the identification of potential biomarkers and enriching the understanding of gene function and regulatory mechanisms. The tutorials, manual, source code, and demo data of ClusterGVis are publicly available at https://github.com/junjunlab/ClusterGVis and https://bioconductor.org/packages/ClusterGVis. The ClusterGVis Shiny app has been deployed on shinyapps.io and is accessible at https://laojunjun.shinyapps.io/clustergvis_app_v0/. The Shiny app source code is hosted on GitHub at https://github.com/junjunlab/ClusterGvis-app.