VST-DAVis: an R Shiny application and web-browser for spatial transcriptomics data analysis and visualization

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Authors: Jagadesan Sankarasubramanian, Chittibabu Guda
Cited by: 0
References: 24

Abstract

Summary: Visium HD Spatial Transcriptomics Data Analysis and Visualization (VST-DAVis) is an interactive, R Shiny application and web browser designed for intuitive analysis of spatial transcriptomics data generated using the 10x Genomics Visium HD platform. This user-friendly tool empowers researchers, particularly those without programming expertise, to perform end-to-end spatial transcriptomics analysis through a streamlined graphical interface. The platform is capable of handling both single and multiple samples, enabling comparative analyses across diverse biological conditions or replicates. It accepts various input formats including both H5 and matrix-based files from Space Ranger and outputs high-quality graphics from various visualization tools. VST-DAVis integrates several widely used R packages, such as Seurat, Monocle3, CellChat, and hdWGCNA, to offer a robust and flexible analytical environment that supports a wide range of analytical tasks, including quality control, clustering, marker gene identification, subclustering, trajectory inference, pathway enrichment analysis, cell-cell communication modeling, co-expression analysis, and transcription factor network reconstruction. By combining its analytical depth with user-friendliness, VST-DAVis makes advanced analyses accessible to various research communities that utilize spatial transcriptomics data. Availability and implementation: VST-DAVis is freely available at https://www.gudalab-rtools.net/VST-DAVis. It is implemented in R 4.5.2 and Bioconductor ≥ 3.22 using the Shiny framework and supports input from Space Ranger outputs. The source code and documentation are hosted on GitHub: https://github.com/GudaLab/VST-DAVis.

Fields of Study & Subjects

Single-cell and spatial transcriptomics Gene expression and cancer classification Genomics and Phylogenetic Studies

Publication details

Journal / source
Bioinformatics Advances
Volume
6
Issue
1
Pages
vbag007–vbag007
Publication date
1 January 2026
Language
EN