3d_OT

Contents:

  • Installation
  • Installation via Github
  • Jupyter Tutorial
  • Single Omics Spatial Domain Identification
    • Spatial Clustering Demonstration of Breast cancer (10xVisium)
    • Spatial Clustering Demonstration of 12 Slices from the DLPFC Dataset(10xVisium)
    • Spatial Clustering Demonstration of mouse visual cortex(Starmap)
  • Multi Omics spatial domain identification
  • Single Omics alignment
  • Mouse brain p(22) alignment
  • 3D reconstruction
  • Cross_platform
3d_OT
  • Single Omics Spatial Domain Identification
  • View page source

Single Omics Spatial Domain Identification

  • Spatial Clustering Demonstration of Breast cancer (10xVisium)
    • Loading package
    • Loading data
    • The ground truth of breast cancer
    • Construct a neighbor graph and train PointNet++Encoder
    • We use mclust for clustering
    • The clustering result of breast cancer
    • Calculate supervision metrics ARI and NMI
  • Spatial Clustering Demonstration of 12 Slices from the DLPFC Dataset(10xVisium)
    • Loading package
    • Loading and Pre-processing 151674 slice data
    • Ground truth of 151674 slice
    • Constructing neighbor graph and training Pointnet++Encoder
    • Clustering with mclust ,Clustering results can be found in adata.obs['3d-OT']
    • 151674 clustering results
    • Quantitative evaluation of clustering performance
    • 151673 slice
    • 151675 slice
    • 151676 slice
    • 151507 slice
    • 151508 slice
    • 151509 slice
    • 151510 slice
    • 151669 slice
    • 151670 slice
    • 151671 slice
    • 151672 slice
  • Spatial Clustering Demonstration of mouse visual cortex(Starmap)
    • Loading package
    • Loading and Pre-processing mouse visual cortex
    • The ground truth of mouse visual cortex
    • Constructing neighbor graph and training Pointnet++Encoder
    • Clustering with mclust ,Clustering results can be found in adata.obs['3d-OT']
    • The clustering result of mouse visual cortex
    • Quantitative evaluation of clustering performance
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