Spatial Transcriptomics

Tutorials for spatial data preprocessing, clustering, deconvolution, downstream analysis, and H&E → ST prediction.

• Preprocessing
  • Crop and Rotation of spatial transcriptomic data
  • Cell Segmentation (10x HD)
  • Analyze NanoString data
  • Analyze Xenium data
  • Analyze 10x Atera (WTA Preview) FFPE breast cancer data
  • Analyze Visium HD data
  • Spatial integration and clustering
  • Preprocess data
  • Training STAligner model
  • Clustering the space
• Clustering
  • Spatial clustering with GraphST + pymclustR
  • Spatial clustering with BINARY + pymclustR
  • Spatial clustering with STAGATE + pymclustR
  • Spatial clustering with CAST + pymclustR
  • Spatial clustering with BANKSY + pymclustR
• Deconvolution
  • Identifying Pseudo-Spatial Map
  • Spatial deconvolution with reference scRNA-seq
  • Spatial deconvolution with RCTD
  • FlashDeconv: Fast Spatial Deconvolution via Structure-Preserving Sketching
  • Spatial deconvolution without reference scRNA-seq
• H&E → spatial transcriptomics prediction (HE-zoo)
  • HEST-FM — pathology foundation model + ridge head
  • STPath — zero-shot generative foundation model
  • STFlow — per-slide flow-matching denoiser
  • iStar — super-resolve a paired Visium + H&E sample
• Downstream
  • Spatial transition tensor of single cells
  • Spatial Communication
  • Spatial IsoDepth Calculation
  • Single cell spatial alignment tools