DeepGFT: clustering spatial transcriptomics data using deep learning and graph Fourier transform

Main

• About
• System Requirements
• Installation
  • Create a virtual environment
  • Install packages
• Data preparation
  • Spatial transcriptomics data
• References
• Release
• DLPFC dataset (151674)
  • 1. Import packages
  • 2. Read data
  • 3. Data processing, including filtering genes and identifying svgs
  • 4. Construct network and GFT
  • 5. Train GAT module
  • 6. Downstream analysis
    • Spatial cluster
    • Gene denoise
• Mouse primary visual cortex dataset
  • 1. Import packages
  • 2. Read data
  • 3. Data processing, including filtering genes and identifying svgs
  • 4. Construct network and GFT
  • 5. Train GAT module
  • 6. Downstream analysis
    • Spatial cluster
    • Gene denoise
• Human breast cancer dataset
  • 1. Import packages
  • 2. Read data
  • 3. Data processing, including filtering genes and identifying svgs
  • 4. Construct network and GFT
  • 5. Train GAT module
  • 6. Downstream analysis
    • Spatial cluster
    • Gene denoise
• Batch: Human breast cancer datasets
  • 1. Import packages
  • 2. Read data
  • 3. Data processing, including filtering genes and identifying svgs
  • 4. Construct network and GFT
  • 5. Train GAT module
  • 6. Downstream analysis
    • Batch effect in two slices
    • Eliminate batch effects and spatial cluster
• Human lymph node dataset
  • 1. Import packages
  • 2. Read data
  • 3. Data processing, including filtering genes and identifying svgs
  • 4. Construct network and GFT
  • 5. Train GAT module
  • 6. Downstream analysis
    • Spatial cluster
    • Gene denoise