deepspot-m
Generate transcriptome-wide virtual spatial transcriptomics from H&E histology with DeepSpot-M. Use when you need spatial gene expression in log1p-CPM for 224x224 tiles at about 20x, want to query protein-coding genes by symbol instead of a fixed panel, or want to run prediction across a whole slide after tiling with histolab.
- Version
- 1.0
- License
- PolyForm-Noncommercial-1.0.0
- Compatibility
- Needs deepspotm 1.0.0 from PyPI (Python 3.10 to 3.13) plus PyTorch. Weights at ratschlab/DeepSpotM on Hugging Face are gated and licensed CC-BY-NC-SA-4.0, so request access on the model page and then run huggingface-cli login. A CUDA GPU speeds up batched inference.
Pinned to revision 70a605012eee, so it is the text this page describes rather than whatever the author pushed since.
Pre-approved tools experimental
Experimental field. Support varies between clients, so this list is what the author declared, not what your client will enforce.
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Files
- skills/deepspot-m/SKILL.md
- skills/deepspot-m/references/api.md
- skills/deepspot-m/references/whole_slide.md
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