Spatial gene expression analysis with SSAM¶
- quick start / tldr page
- Installation
- Data Preparation
- Creating the vector field
- The shape of the kernel
- Kernel bandwidth
- Input masks
- SSAM guided analysis
- Thresholding the guided cell-type map
- SSAM de novo analysis
- Filtering local maxima
- Filtering “stray” local maxima using k-nearest neighbour density
- Clustering Local L-1 Maxima
- Diagnostic plots
- Cluster annotation
- Thresholding the de-novo cell-type map
- Visualisation of 2D gene expression embeddings (t-SNE and UMAP)
- Identifying tissue domains
- Cell-type composition analysis in tissue domains
- Experimental features
- Cell-type classification using Adversarial Autoencoders
- Segmenting the SSAM cell type map