Current cell annotation methods using high-plex spatial proteomics data are resource intensive and demand iterative expert input. Here, the authors present MAPS (Machine learning for Analysis of Proteomics in Spatial biology), an approach that facilitates rapid and precise cell type identification with human-level accuracy from spatial proteomics data.
- Muhammad Shaban
- Yunhao Bai
- Faisal Mahmood
