Multi Omics spatial domain identification

• Spatial multi-omics Clustering Demonstration of five simulated data
  • Loading package
  • Loading Simulation data1
  • Simulation Data 2
  • Simulation Data 3
  • Simulation Data 4
  • Simulation Data 5
• Spatial multi-Omics Clustering Demonstration of Human_Lymph_Node A1
  • Loading package
  • Loading data
  • Constructing the neighbor graph and training the PointNet++ Encoder
  • We use mclust for clustering
  • The clustering result
  • Calculation of six types of supervision indicators
• Data integration for mouse brain Spatial-epigenome-transcriptome
  • Loading package
  • Loading data
  • Pre-processing data
  • Constructing neighbor graph and training the PointNet++Encoder1
  • Constructing neighbor graph and training the PointNet++Encoder2
  • Obtain the fusion feature representation of ATAC+RNA
  • After integration, we perform clustering analysis using the fusion feature representation
  • Calculate ARI using manual annotation
  • Obtain the fusion feature representation of H3K27ac+RNA
  • H3K4me3+RNA
  • H3K27me3+RNA