Tutorials
Here are the tutorials for the demo datasets .
To run the tutorials, first please download the demo data and pretrained model checkpoints file from:
google drive: https://drive.google.com/drive/folders/1z1nk0sF_e25LKMyHxJVMtROFjuWet2G_?usp=sharing
Please place both ‘checkpoints’ and ‘demo’ folder under the ‘S2Omics’ main folder.
We offer four tutorials handling diverse cases:
Tutorial 1 is about designing VisiumHD experiment on a colorectal cancer section, including ROI selection and cell type label broadcasting
Tutorial 2 is about designing CosMx experiment on two kidney sections (a healthy one and a T2D one), including both ROI and FOV selection
Tutorial 3 is about designing spatial omics experiment on three consecutive breast cancer sections, including ROI selection
Tutorial 4 is about designing TMA experiment on a slide containing multiple breast cancer biopsyes, this tutorial includes circle-shaped ROI selection
Tutorials
- Tutorial 1: Design VisiumHD experiment for a colorectal cancer section
- Step 1: Preprocess the H&E image
- Step 2: Quality control for all superpixels
- Step 3: Histology feature extraction
- Step 4: Histology segmentation
- Step 5: Merge over-clusters
- Step 6: Select best ROI for VisiumHD experiment
- (Optional) Step 7: Cell type label broadcasting
- Tutorial 2: Design CosMx experiment for 2 kidney sections
- Step 1: Preprocess the H&E image
- Step 2: Quality control for all superpixels
- Step 3: Histology feature extraction
- Step 4: Histology segmentation
- Step 5: Merge over-clusters
- Step 6: Select best ROI for CosMx experiment
- Step 6: Select best FOV for CosMx experiment
- Tutorial 3: Design spatial omics experiment for consecutive breast cancer sections
- Step 1: Preprocess the H&E image
- Step 2: Quality control for all superpixels
- Step 3: Histology feature extraction
- Step 4: Joint histology segmentation
- Step 5: Select best ROI for spatial omics experiment
- Tutorial 4: Design Tissue Micro Array experiment for multiple breast biopsies
- Step 1: Preprocess the H&E image
- Step 2: Quality control for all superpixels
- Step 3: Histology feature extraction
- Step 4: Histology segmentation
- Step 5: Merge over-clusters
- Step 6: Select best ROI for TMA experiment