VST-DAVis

VST-DAVis is a user-friendly, browser-based R Shiny application designed for researchers without programming expertise to analyze and visualize 10x Genomics Spatial Transcriptomics Visium HD. It supports single and multiple sample analyses as well as group comparisons, offering a range of functionalities for comprehensive data exploration.

Features

VST-DAVis includes nine functional modules:

1. Single or Multiple Samples Analysis
   • Stats
   • Sample Groups and QC Filtering
   • Normalization and PCA Analysis
   • Clustering
   • Marker Identification
   • Cell Type Prediction
   • Cluster-Based Plots
   • Condition-Based Analysis
2. Subclustering
3. Correlation Network Analysis
4. Genome Ontology (GO) Terms
5. Pathway Analysis
6. GSEA Analysis
7. Cell-Cell Communication
8. Trajectory and Pseudotime Analysis
9. Co-Expression and TF Analysis
   • Co-Expression Network Analysis
   • Transcription Factor Regulatory Network Analysis

Use VST-DAVis Online

VST-DAVis is deployed online and accessible at:
https://www.gudalab-rtools.net/VST-DAVis

Launch VST-DAVis Locally

Prerequisites

Ensure the following software is installed:

• R (>= 4.5.0): Download R
• RStudio (>= 2024.12.1): Download RStudio
• Bioconductor (>= 3.21)
• Shiny (>= 1.10.0)

Note: VST-DAVis has been tested with these versions. Using older versions of R may cause errors during package installation. Updating to the latest R version is recommended.

Installation

Run the following commands in an R session to install required packages:

if (!require("BiocManager")) install.packages("BiocManager", update = FALSE)
if (!require("devtools")) install.packages("devtools", update = FALSE)

# Function to check and install CRAN packages
install_cran_packages <- function(packages) {
  for (pkg in packages) {
    if (!require(pkg, character.only = TRUE)) {
      install.packages(pkg, dependencies = TRUE)
    }
  }
}

# Function to check and install Bioconductor packages
install_bioc_packages <- function(packages) {
  for (pkg in packages) {
    if (!require(pkg, character.only = TRUE)) {
      BiocManager::install(pkg, update = FALSE, dependencies = TRUE)
    }
  }
}

# Function to check and install GitHub packages
install_github_packages <- function(packages) {
  for (pkg in names(packages)) {
    if (!require(pkg, character.only = TRUE)) {
      devtools::install_github(packages[[pkg]], upgrade = "never", dependencies = TRUE)
    }
  }
}

# List of CRAN packages
cran_packages <- c("shiny", "DT", "shinythemes", "shinyjs", "shinyFiles", "shinyWidgets", "shinycssloaders", "ggplot2", "data.table", "ggpubr", "shinydashboard", "dplyr", "tibble", "HGNChelper", "openai", "metap", "ggrepel", "R.utils", "circlize", "hdf5r", "ggupset", "gridExtra", "ggalluvial", "NMF", "ggraph", "igraph", "cowplot", "pdftools", "xgboost", "msigdbr")

if (!require("msigdbdf"))install.packages("msigdbdf", repos = "https://igordot.r-universe.dev")

# List of Bioconductor packages
bioc_packages <- c("Seurat", "SeuratObject", "sctransform", "celldex", "SingleR", "scRNAseq", "glmGamPoi", "scran", "EnhancedVolcano", "ComplexHeatmap", "clusterProfiler", "org.Hs.eg.db", "org.Mm.eg.db", "org.Mmu.eg.db", "org.Rn.eg.db", "org.Ss.eg.db", "ReactomePA", "fgsea", "enrichplot", "multtest", "WGCNA", "hdWGCNA", "motifmatchr", "TFBSTools", "GenomicRanges", "JASPAR2020", "JASPAR2024", "EnsDb.Hsapiens.v86", "BSgenome.Hsapiens.UCSC.hg38", "BSgenome.Mmusculus.UCSC.mm10")

# List of GitHub packages
github_packages <- list(
  "GPTCelltype" = "Winnie09/GPTCelltype",
  "openxlsx" = "ycphs/openxlsx",
  "presto" = "immunogenomics/presto",
  "monocle3" = "cole-trapnell-lab/monocle3",
  "SeuratWrappers" = "satijalab/seurat-wrappers",
  "SeuratDisk" = "mojaveazure/seurat-disk",
  "patchwork" = "thomasp85/patchwork",
  "CellChat" = "jinworks/CellChat",
  "genesorteR" = "mahmoudibrahim/genesorteR",
  "hdWGCNA" = "smorabit/hdWGCNA"
)

# Install all packages
install_cran_packages(cran_packages)
install_bioc_packages(bioc_packages)
install_github_packages(github_packages)

Start the App

To launch VST-DAVis, follow one of these methods:

Option 1: Run Directly from GitHub

1. Open an R session in RStudio.
2. Execute the following lines of code:

library(shiny)
shiny::runGitHub('VST-DAVis', 'GudaLab')

Option 2: Download the source code from GitHub and run:

library(shiny)
runApp('/path/to/the/VST-DAVis-master', launch.browser = TRUE)

Replace /path/to/the/VST-DAVis-master with the actual path to the downloaded folder

Usage

A detailed user manual is available under the "Manual" tab at: https://www.gudalab-rtools.net/VST-DAVis

Example Datasets

To ensure seamless analysis and reproducibility, VST-DAVis includes one reference dataset for each input format. These datasets, sourced from NCBI, have been pre-tested with the tool and allow users to explore its functionalities and understand the analysis workflow effectively.

Available Datasets:

• H5 File: GSE230207
• Matrix Files: GSE244014

These datasets are ideal for:

• Demonstrating VST-DAVis functionalities.
• Familiarizing users with the tool's analysis workflow.
• Testing the application in different input formats.

Users can download these datasets directly from the provided links and use them to explore VST-DAVis. Users who download sample files from NCBI or other public repositories need to rename and organize their files to match the Space Ranger output format, which is required by our application.

So We have also included example datasets in both supported formats to guide users:

• H5 + Spatial folder format P1_ON1_A.zip
• Space Ranger Matrix, Feature, Barcode, and Spatial image files format control_e14_3.zip

Users can download and extract these example files directly from the GitHub repository or from the upload page of the application. This will help users correctly format their data and ensure full compatibility with our tool.

Tested Platforms

This application was tested on: Linux (Red Hat and Ubuntu) and Windows (10 and 11)